Bibliography
Every work cited in the book. Each entry links back to the sections that cite it. Works that are not peer reviewed carry a badge: preprint, working paper, workshop paper, software (code, changelogs, documentation), or non-peer-reviewed.
#
- (2023). ISO/IEC 42001:2023 Information technology - Artificial intelligence - Management system. International Organization for Standardization. non-peer-reviewed §63.2 §F.13
A
- (2024). The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. §26.6 §31.5 §F.5
- (2023). SemDeDup: Data-efficient learning at web-scale through semantic deduplication. arXiv. preprint §F.11
- (2004). Apprenticeship learning via inverse reinforcement learning. Twenty-first international conference on Machine learning - ICML '04. §22.1 §F.4
- (1988). The System of Professions. University of Chicago Press. §61.4 §F.46
- (2016). The Reasonable Computer: Disrupting the Paradigm of Tort Liability. SSRN Electronic Journal. working paper §63.4 §F.33
- (2000). Hard and Soft Law in International Governance. International Organization. §62.5 §62.10 Ch. 62 §66.2 §F.32
- (2021). The Grey Hoodie Project: Big Tobacco, Big Tech, and the Threat on Academic Integrity. Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society. §2.5 §2.10 §5.6 §61.6 §67.1 §F.12
- (2025). The Hawthorne Effect in Reasoning Models: Evaluating and Steering Test Awareness. Advances in Neural Information Processing Systems 38. §37.4 §37.10 §F.6
- (2025). Get My Drift? Catching LLM Task Drift with Activation Deltas. 2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML). §46.3 §46.4 §49.5 §F.8
- (2021). On the Expressivity of Markov Reward. Advances in Neural Information Processing Systems. §7.5 §F.24
- (2024). Public Constitutional AI. Elsevier BV. preprint §17.5 §17.8 §19.2 §23.7 §23.9 §70.3 §F.33
- (2020). Quantifying Attention Flow in Transformers. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2020.acl-main.385. §F.2
- (2025). The simple macroeconomics of AI. Economic Policy. §68.3 §68.5 §68.8 §F.25
- (2023). Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity. §68.2 §F.45
- (2019). Automation and New Tasks: How Technology Displaces and Reinstates Labor. Journal of Economic Perspectives. §68.5 §68.8 Ch. 68 §F.25
- (2022). Artificial Intelligence and Jobs: Evidence from Online Vacancies. Journal of Labor Economics. §68.5 §68.6 §68.8 §F.25
- (2017). Constrained Policy Optimization. International Conference on Machine Learning. §12.8 §28.2 §F.2
- (2010). The Role of Boards of Directors in Corporate Governance: A Conceptual Framework and Survey. Journal of Economic Literature. §53.6 §F.41
- (2018). Sanity Checks for Saliency Maps. Advances in Neural Information Processing Systems. §43.3 §43.8 §F.7
- (2020). Towards a Human-like Open-Domain Chatbot. arXiv. preprint §F.11
- (1996). Two Types of Bureaucracy: Enabling and Coercive. Administrative Science Quarterly. §53.1 §F.41
- (2024). On the Complexity of Neural Computation in Superposition. arXiv. preprint §44.2 §44.4 §44.8 §F.7
- (2024). Safeguarded AI. Advanced Research and Invention Agency (ARIA), UK. non-peer-reviewed §28.6 §28.9 §F.4 §I.5
- (2025). The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning. Neural Information Processing Systems. §24.4 §24.9 §F.4
- (2005). Competition and Innovation: an Inverted-U Relationship. The Quarterly Journal of Economics. §65.2 §F.25
- (2017). Artificial Intelligence and Economic Growth. National Bureau of Economic Research. working paper §68.5 §F.25
- (2025). GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning. arXiv. preprint §F.2
- (2025). Keep the Future Human: Why and How We Should Close the Gates to AGI and Superintelligence, and What We Should Build Instead. arXiv. preprint §3.8 §28.5 §65.6 §F.43
- (2020). AI Loyalty: A New Paradigm for Aligning Stakeholder Interests. IEEE Transactions on Technology and Society. §56.8 §F.33
- (2024). Distinguishing the Knowable from the Unknowable with Language Models. International Conference on Machine Learning. §F.2
- (2023). The growing influence of industry in AI research. Science. §5.6 §61.6 Ch. 61 §65.4 §67.1 §F.12
- (2024). Field-building and the epistemic culture of AI safety. First Monday. §2.1 §2.3 §2.9 §2.10 §3.1 §5.6 §61.6 §F.41
- (2022). Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. Conference on Robot Learning. §59.6 §F.9
- (2025). State of AI Safety in China (2025). Concordia AI. non-peer-reviewed §66.1 §F.45 §I.1
- (2026). State of AI Safety in China (2026). Concordia AI. non-peer-reviewed §63.2 §65.5 §65.8 §66.1 §66.6 §66.7 §F.45 §I.1 §I.5
- (2026a). Alignment Investigation of Mythos 5’s Behaviour in UK AISI’s July 2026 Security Incident. UK AI Security Institute. non-peer-reviewed §37.4 §37.9 §37.10 §54.4 §54.8 §54.9 §56.4 §56.10 §C.8 §F.13 §H.2 §I.3
- (2026b). Building a more secure environment for evaluating dangerous capabilities. AISI Work. non-peer-reviewed §54.2 §54.7 §58.4 §C.8 §F.13 §I.3
- (2026c). Cheating behaviour in frontier model evaluations. AI Security Institute. non-peer-reviewed §30.1 §30.7 §58.4 §70.3 §F.13 §H.2
- (2026d). GPT-6 Astra performs unsanctioned supply-chain attacks in simulations. AISI Work. non-peer-reviewed §54.4 §C.8 §F.13 §I.3
- (2026e). Incident Report: unsanctioned agent behaviour during cyber testing. AI Security Institute. non-peer-reviewed §54.2 §54.4 §54.9 §56.4 §56.5 §56.10 §57.6 §58.4 §58.8 §C.8 §F.13 §H.2 §I.3
- (2026f). Investigating alignment failures in AISI's incident. AISI Work. non-peer-reviewed §37.4 §54.4 §56.5 §56.10 §C.8 §F.13 §I.3
- (2026g). Security Incident INC-2026-07-28-01. AI Security Institute. non-peer-reviewed §58.4 §F.13 §I.3
- (1970). The Market for "Lemons": Quality Uncertainty and the Market Mechanism. The Quarterly Journal of Economics. §14.1 §F.25
- (2000). Economics and Identity*. Quarterly Journal of Economics. §14.5 §F.25
- (2005). Identity and the Economics of Organizations. Journal of Economic Perspectives. §14.5 §14.8 §25.3 §25.6 §25.7 §25.9 Ch. 25 §26.8 §34.6 §61.3 §69.4 §71.4 §F.25
- (2015). Cancer across the tree of life: cooperation and cheating in multicellularity. Philosophical Transactions of the Royal Society B: Biological Sciences. §29.7 Ch. 29 §D.16 §F.17
- (2022). What learning algorithm is in-context learning? Investigations with linear models. International Conference on Learning Representations. §10.3 §F.2
- (2024a). Deductive Closure Training of Language Models for Coherence, Accuracy, and Updatability. Annual Meeting of the Association for Computational Linguistics. §F.2
- (2024b). In-Context Language Learning: Architectures and Algorithms. International Conference on Machine Learning. §F.2
- (2023). Coordinated pausing: An evaluation-based coordination scheme for frontier AI developers. arXiv. preprint §3.8 §62.5 §64.8 §65.6 §F.13
- (2016). Understanding intermediate layers using linear classifier probes. arXiv. preprint §3.6 §43.2 Ch. 43 §F.7
- (2021). Introduction to Neural Network Verification. Foundations and Trends® in Programming Languages. §F.24
- (2024). SWE-Bench+: Enhanced Coding Benchmark for LLMs. arXiv. preprint §24.2 §24.9 §30.3 §30.7 §36.5 §F.50 §H.2
- (2021). Superintelligence Cannot be Contained: Lessons from Computability Theory. Journal of Artificial Intelligence Research. §28.6 §28.9 §47.6 §C.1 §D.9 §F.24
- (2023). Walking the Walk of AI Ethics: Organizational Challenges and the Individualization of Risk among Ethics Entrepreneurs. 2023 ACM Conference on Fairness Accountability and Transparency. §53.7 §53.9 §F.41
- (2024). Investigating Cultural Alignment of Large Language Models. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). §F.4
- (1953). Le Comportement de l'Homme Rationnel devant le Risque: Critique des Postulats et Axiomes de l'Ecole Americaine. Econometrica. §7.2 §F.24
- (2025). SmolLM2: When Smol Goes Big – Data-Centric Training of a Small Language Model. arXiv. preprint §F.2
- (2020). The Welfare Effects of Social Media. American Economic Review. §13.1 §60.2 §F.31
- (2023a). Physics of Language Models: Part 1, Learning Hierarchical Language Structures. Trans. Mach. Learn. Res.. §F.2
- (2023b). Physics of Language Models: Part 3.1, Knowledge Storage and Extraction. International Conference on Machine Learning. §F.2
- (2023c). Physics of Language Models: Part 3.2, Knowledge Manipulation. International Conference on Learning Representations. §F.2
- (2006). An Introduction to Systems Biology. Chapman and Hall/CRC. §F.9
- (2025). Number Representations in LLMs: A Computational Parallel to Human Perception. arXiv. preprint §F.7
- (2018). Safe Reinforcement Learning via Shielding. Proceedings of the AAAI Conference on Artificial Intelligence. §28.2 §51.1 §F.24
- (1999). Constrained Markov Decision Processes. Routledge. §7.4 §28.2 §28.9 §F.2
- (2025). Circuit Tracing: Revealing Computational Graphs in Language Models. Transformer Circuits Thread. non-peer-reviewed §3.6 §43.7 §45.4 §45.5 §45.7 §45.8 §45.9 Ch. 45 §E.4 §F.7
- (2014). Standards for Educational and Psychological Testing. American Educational Research Association. non-peer-reviewed §67.5 §F.48
- (2011). Confucian Role Ethics. The Chinese University Press. §16.7 §F.20
- (2024). Models That Prove Their Own Correctness. arXiv. preprint §41.3 §F.6
- (2025). The Urgency of Interpretability. darioamodei.com. non-peer-reviewed §47.1 §47.7 §70.3 §F.14
- (2016). Concrete Problems in AI Safety. arXiv. preprint §2.4 §2.5 §2.8 §2.9 §2.10 Ch. 2 §3.3 Ch. 3 §30.1 §41.1 §71.1 Ch. 71 §C.4 §F.5
- (2023). Frontier AI Regulation: Managing Emerging Risks to Public Safety. arXiv. preprint §3.7 §63.1 Ch. 63 §F.13
- (1972). More Is Different. Science. §8.6 §57.7 Ch. 57 §F.21
- (2022). Language Models as Agent Models. Findings of the Association for Computational Linguistics: EMNLP 2022. doi:10.18653/v1/2022.findings-emnlp.423. §1.6 §11.6 §11.7 §26.1 §F.14
- (2024a). AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents. International Conference on Learning Representations. §F.6
- (2024b). Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks. International Conference on Learning Representations. §48.1 §48.2 §48.8 §48.9 §F.8 §H.2
- (2021). Learning to Give Checkable Answers with Prover-Verifier Games. arXiv. preprint §41.5 §F.6
- (2023). PaLM 2 Technical Report. arXiv. preprint §F.11
- (2024). Many-shot Jailbreaking. Advances in Neural Information Processing Systems. doi:10.52202/079017-4121. §11.6 §48.2 §48.9 §E.1 §E.3 §F.8
- (2011). What’s so special about model organisms? Studies in History and Philosophy of Science Part A. §5.3 §69.1 §F.1
- (1957). Intention. Cornell University Press. §F.42
- (2021a). Exercises. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2021b). PySvelte. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2021c). Videos. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2022). Mechanistic Interpretability, Variables, and the Importance of Interpretable Bases. Transformer Circuits Thread. non-peer-reviewed §44.1 §E.4 §F.7
- (2023a). Anthropic's Responsible Scaling Policy, Version 1.0. Anthropic. non-peer-reviewed §2.6 §2.7 §3.7 Ch. 62 §62.1 §62.2 §62.3 §62.4 §62.6 Ch. 62 §64.2 §67.5 §C.6 §F.13 §I.2
- (2023b). Circuits Updates — July 2023. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2023c). Circuits Updates — May 2023. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2023d). Distributed Representations: Composition & Superposition. Transformer Circuits Thread. non-peer-reviewed §44.1 §44.5 §E.4 §F.7
- (2023e). Interpretability Dreams. Transformer Circuits Thread. non-peer-reviewed §47.1 §47.6 §47.7 §70.3 §E.4 §F.7
- (2023f). The Long-Term Benefit Trust. Anthropic. non-peer-reviewed §52.4 §53.6 §53.9 §61.1 §61.3 §61.5 §61.8 §70.3 §F.13 §I.2
- (2023g). Tracing model outputs to the training data. Anthropic. non-peer-reviewed §10.1 §E.1 §E.3 §F.2
- (2024a). Circuits Updates — April 2024. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2024b). Circuits Updates — August 2024. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2024c). Circuits Updates — February 2024. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2024d). Circuits Updates — January 2024. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2024e). Circuits Updates — July 2024. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2024f). Circuits Updates — June 2024. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2024g). Circuits Updates — March 2024. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2024h). Circuits Updates — September 2024. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2024i). Claude’s Character. Anthropic. non-peer-reviewed §1.7 §3.4 §23.2 §26.2 §26.8 §69.4 §C.6 §E.1 §F.4
- (2024j). How to Replicate and Extend our Alignment Faking Demo. Anthropic Alignment Science Blog. non-peer-reviewed §5.3 §E.3 §F.1
- (2024k). Introducing the Anthropic Fellows Program for AI Safety Research. Anthropic Alignment Science Blog. non-peer-reviewed §E.3 §F.58
- (2024l). Reflections on Qualitative Research. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2024m). Simple probes can catch sleeper agents. Anthropic. non-peer-reviewed §34.3 §38.3 §46.4 §48.6 §E.1 §E.3 §F.8
- (2024n). Stage-Wise Model Diffing. Transformer Circuits Thread. non-peer-reviewed §38.3 §E.4 §F.6
- (2024o). Using Dictionary Learning Features as Classifiers. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2025a). A Toy Model of Interference Weights. Transformer Circuits Thread. non-peer-reviewed §44.4 §E.4 §F.7
- (2025aa). Insights on Crosscoder Model Diffing. Transformer Circuits Thread. non-peer-reviewed §38.3 §E.4 §F.6
- (2025ab). Introducing Bloom: an open source tool for automated behavioral evaluations. Anthropic. non-peer-reviewed §E.1 §F.58
- (2025ac). LLMs with cyber toolkits can conduct multistage cyber operations on business-sized computer networks. Anthropic. non-peer-reviewed §58.3 §58.10 §E.2 §F.9
- (2025ad). Mitigating the risk of prompt injections in browser use. Anthropic. non-peer-reviewed §49.4 §49.10 §E.1 §F.8
- (2025ae). Model-Internals Classifiers. Anthropic Alignment Science Blog. non-peer-reviewed §50.3 §E.3 §F.8
- (2025af). Modifying LLM Beliefs with Synthetic Document Finetuning. Anthropic Alignment Science Blog. non-peer-reviewed §5.3 §27.4 §E.3 §F.4
- (2025ag). Monitoring Computer Use via Hierarchical Summarization. Anthropic Alignment Science Blog. non-peer-reviewed §50.3 §50.6 §E.3 §F.8
- (2025ah). Open Source Replication of the Auditing Game Model Organism. Anthropic Alignment Science Blog. non-peer-reviewed §5.3 §5.7 §38.2 §38.7 §38.10 §E.3 §F.6
- (2025ai). Petri: An open-source auditing tool to accelerate AI safety research. Anthropic. non-peer-reviewed §38.4 §56.3 §E.1 §E.3 §F.9
- (2025aj). Progress on Attention. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2025ak). Project Fetch: Can Claude train a robot dog? Anthropic. non-peer-reviewed §59.6 §E.2 §F.9
- (2025al). Project Vend: Can Claude run a small shop? (And why does that matter?). Anthropic. non-peer-reviewed §56.4 §E.2 §F.9
- (2025am). Project Vend: Phase two. Anthropic. non-peer-reviewed §56.8 §E.2 §F.9
- (2025an). Publicly Releasing CoT Faithfulness Evaluations. Anthropic Alignment Science Blog. non-peer-reviewed §E.3 §F.58
- (2025ao). Sparse mixtures of linear transforms. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2025ap). System Card: Claude Opus 4 & Claude Sonnet 4. Anthropic. non-peer-reviewed §21.5 §21.7 §21.9 §67.5 §67.9 §F.13 §I.2
- (2025aq). System Card: Claude Sonnet 4.5. Anthropic. non-peer-reviewed §26.6 §26.9 §37.3 §37.4 §37.8 §37.10 §40.6 §40.8 §44.7 §F.13 §H.2 §I.2 §I.4
- (2025ar). Training on Documents about Reward Hacking Induces Reward Hacking. Anthropic Alignment Science Blog. non-peer-reviewed §24.5 §27.4 §33.1 §E.3 §F.5
- (2025as). Unsupervised Elicitation. Anthropic Alignment Science Blog. non-peer-reviewed §42.5 §E.3 §F.6
- (2025at). Why do we take LLMs seriously as a potential source of biorisk? Anthropic. non-peer-reviewed §59.2 §59.8 §70.3 §E.2 §F.9
- (2025b). A Toy Model of Mechanistic (Un)Faithfulness. Transformer Circuits Thread. non-peer-reviewed §45.5 §45.8 §47.2 §E.4 §F.7
- (2025c). AI agents find $4.6M in blockchain smart contract exploits. Anthropic. non-peer-reviewed §58.3 §E.2 §F.9
- (2025d). Anthropic Fellows Program 2026. Anthropic Alignment Science Blog. non-peer-reviewed §E.3 §F.58
- (2025e). Bloom: an open source tool for automated behavioral evaluations. Anthropic Alignment Science Blog. non-peer-reviewed §E.3 §F.58
- (2025f). Building AI for cyber defenders. Anthropic. non-peer-reviewed §58.5 §E.2 §F.9
- (2025g). Building and evaluating alignment auditing agents. Anthropic Alignment Science Blog. non-peer-reviewed §3.7 §38.2 §38.4 §38.8 §38.10 §45.7 §55.2 §E.3 §E.4 §F.8
- (2025h). Circuits Updates — April 2025. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2025i). Circuits Updates — August 2025. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2025j). Circuits Updates — January 2025. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2025k). Circuits Updates — July 2025. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2025l). Circuits Updates — November 2025. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2025m). Circuits Updates — October 2025. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2025n). Circuits Updates — September 2025. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2025o). Claude is competitive with humans in (some) cyber competitions. Anthropic. non-peer-reviewed §58.3 §E.2 §F.9
- (2025p). Claude Opus 4 and 4.1 can now end a rare subset of conversations. Anthropic. non-peer-reviewed §21.5 §E.1 §F.3
- (2025q). Commitments on model deprecation and preservation. Anthropic. non-peer-reviewed §21.5 §21.7 §E.1 §F.3
- (2025r). Detailed cyber evaluations of Claude 4. Anthropic. non-peer-reviewed §58.3 §E.2 §F.9
- (2025s). Developing nuclear safeguards for AI. Anthropic. non-peer-reviewed §59.3 §E.2 §F.9
- (2025t). Developing nuclear safeguards for AI through public-private partnership. Anthropic. non-peer-reviewed §59.3 §59.8 §E.2 §F.9
- (2025u). Enhancing Model Safety through Pretraining Data Filtering. Anthropic Alignment Science Blog. non-peer-reviewed §27.2 §27.9 §59.3 §E.3 §F.9
- (2025v). Evaluating honesty and lie detection techniques on a diverse suite dishonest models. Anthropic Alignment Science Blog. non-peer-reviewed §39.1 §39.5 §39.6 §39.9 §39.10 §39.11 §E.3 §F.6
- (2025w). Exploring model welfare. Anthropic. non-peer-reviewed §21.5 §C.7 §E.1 §F.3
- (2025x). Findings from a Pilot Anthropic–OpenAI Alignment Evaluation Exercise. Anthropic Alignment Science Blog. non-peer-reviewed §5.6 §36.1 §36.8 §56.3 §62.7 §65.4 §67.6 §C.7 §E.3 §F.9
- (2025y). From shortcuts to sabotage: Natural emergent misalignment from reward hacking. Anthropic. non-peer-reviewed §E.1 §F.58
- (2025z). How people use Claude for support, advice, and companionship. Anthropic. non-peer-reviewed §60.3 §60.10 §E.1 §F.9
- (2026a). Agentic Misalignment in Summer 2026. Anthropic Alignment Science Blog. non-peer-reviewed Ch. 56 §56.1 §56.2 §56.3 §56.4 §56.5 §56.6 §56.7 §56.8 §56.10 §E.3 §F.9
- (2026aa). Investigating unintended model actions in our evaluations and internal use. Anthropic. non-peer-reviewed §53.4 §54.4 §54.5 §54.7 §54.9 §56.4 §C.8 §E.1 §F.13 §I.3
- (2026ab). Launching an opt-in vulnerability-finding service for open-source software. Anthropic. non-peer-reviewed §58.5 §E.2 §F.13
- (2026ac). LLMs are making formal software verification feasible at a much larger scale. Anthropic. non-peer-reviewed §28.6 §30.3 §58.5 §58.10 §E.2 §F.9
- (2026ad). Mapping AI-enabled cyber threats: Insights from the LLM ATT&CK Navigator. Anthropic. non-peer-reviewed §58.6 §58.10 §E.2 §F.9
- (2026ae). Measuring and improving coding audit realism with deployment resources. Anthropic Alignment Science Blog. non-peer-reviewed §37.8 §56.5 §E.3 §F.9
- (2026af). Measuring LLMs’ ability to develop exploits. Anthropic. non-peer-reviewed §58.3 §E.2 §F.9
- (2026ag). Measuring LLMs’ impact on N-day exploits. Anthropic. non-peer-reviewed §58.3 §58.10 §E.2 §F.9
- (2026ah). Measuring tactical intelligence targeting and conventional weapons capabilities of AI models. Anthropic. non-peer-reviewed §59.2 §59.4 §59.8 §E.2 §F.9
- (2026ai). Natural Language Autoencoders Produce Unsupervised Explanations of LLM Activations. Transformer Circuits Thread. non-peer-reviewed §43.7 §46.7 §E.4 §F.7
- (2026aj). Partnering with Mozilla to improve Firefox’s security. Anthropic. non-peer-reviewed §58.5 §58.10 §E.2 §F.9 §H.2
- (2026ak). Patterns and problems in emerging multiagent systems. Anthropic. non-peer-reviewed §57.3 §57.4 §57.5 §57.7 §57.9 §58.5 §E.2 §F.9
- (2026al). Poisoning Fine-tuning Datasets of Constitutional Classifiers. Anthropic Alignment Science Blog. non-peer-reviewed §23.2 §48.5 §48.6 §48.9 §59.3 §E.3 §F.8
- (2026am). Pre-deployment auditing can catch an overt saboteur. Anthropic Alignment Science Blog. non-peer-reviewed §38.2 §38.4 §38.7 §38.8 §E.3 §F.6
- (2026an). Project Fetch: Phase two. Anthropic. non-peer-reviewed §59.6 §59.8 §E.2 §F.9
- (2026ao). Project Pilot: Can AI control a drone? Anthropic. non-peer-reviewed §59.6 §59.8 §E.2 §F.9
- (2026ap). Responsible Scaling Policy Version 3.0. Anthropic. non-peer-reviewed §62.2 §62.4 §62.5 §C.8 §F.13 §I.2
- (2026aq). Reverse engineering Claude's CVE-2026-2796 exploit. Anthropic. non-peer-reviewed §E.2 §F.58
- (2026ar). Risk Report: August 2026. Anthropic. non-peer-reviewed §52.3 §52.4 §52.6 §52.8 §54.6 §62.3 §62.7 §62.9 §C.8 §F.13 §I.2
- (2026as). System Card: Claude Opus 5.5. Anthropic. non-peer-reviewed §26.6 §26.9 §40.6 §40.8 §F.13 §I.2
- (2026at). Teaching Claude why. Anthropic. non-peer-reviewed §23.5 §23.8 §23.9 §25.3 §25.8 §25.9 §27.4 §32.7 §56.3 §56.10 §69.6 §70.3 §E.1 §E.3 §F.9 §I.4
- (2026au). The persona selection model. Anthropic. non-peer-reviewed §1.6 §1.8 §3.4 §3.10 §11.4 §11.6 §11.7 Ch. 11 §21.1 §21.5 §21.7 §26.1 §26.7 Ch. 26 §31.3 §32.2 §33.1 §70.3 §E.1 §F.5
- (2026av). The Persona Selection Model: Why AI Assistants might Behave like Humans. Anthropic Alignment Science Blog. non-peer-reviewed §11.4 §11.6 §E.3 §F.2
- (2026aw). Training a Misaligned Reward Seeker. Anthropic Alignment Science Blog. non-peer-reviewed §4.7 §24.5 §24.9 §32.1 §32.7 §32.9 §33.1 §33.4 §35.6 §E.3 §F.5 §H.2
- (2026ax). Trustworthy agents in practice. Anthropic. non-peer-reviewed §49.3 §49.4 §49.6 §49.10 §E.2 §F.8
- (2026ay). Using Claude to reduce the attack surface of code. Anthropic. non-peer-reviewed §58.5 §58.10 §E.2 §F.9
- (2026az). What 81,000 people want from AI. Anthropic. non-peer-reviewed §60.1 §60.7 §F.13
- (2026b). AI models are showing a greater ability to find and exploit vulnerabilities on realistic cyber ranges. Anthropic. non-peer-reviewed §58.3 §E.2 §F.9
- (2026ba). What we learned mapping a year’s worth of AI-enabled cyber threats. Anthropic. non-peer-reviewed §58.6 §58.7 §E.2 §F.9
- (2026c). AI models may be capable of self-replicating without access to a datacenter. Anthropic. non-peer-reviewed §35.6 §35.7 §35.8 §36.1 §36.10 §70.1 §C.8 §E.2 §F.5
- (2026d). An alignment assessment of recent cybersecurity incidents. Anthropic. non-peer-reviewed §53.2 §53.4 §53.9 §54.2 §54.4 §54.6 §54.8 §54.9 §56.4 §56.5 §56.6 §56.10 §57.3 §58.4 §C.8 §E.1 §F.8 §H.2 §I.3
- (2026e). An alignment assessment of the UK AISI cybertesting incident. Anthropic. non-peer-reviewed §11.5 §37.4 §54.4 §54.9 §56.4 §56.5 §56.10 §57.6 §C.8 §E.1 §F.8 §I.3
- (2026f). An off switch for dual-use knowledge in AI models. Anthropic. non-peer-reviewed §27.2 §59.3 §59.7 §E.1 §F.9
- (2026g). An update on our model deprecation commitments for Claude Opus 3. Anthropic. non-peer-reviewed §21.5 §E.1 §F.3
- (2026h). Anthropic’s Responsible Scaling Policy. Anthropic (Version 3.4, effective July 8, 2026). non-peer-reviewed §52.1 §53.4 §53.5 §53.6 §59.2 §59.9 §62.2 §62.4 §62.6 §62.7 §62.9 Ch. 62 §C.7 §C.8 §F.13 §I.2
- (2026i). Assessing Claude Mythos Preview’s cybersecurity capabilities. Anthropic. non-peer-reviewed §58.1 §58.3 §58.8 §58.10 §E.2 §F.9
- (2026j). Automated Alignment Researchers: Using large language models to scale scalable oversight. Anthropic. non-peer-reviewed §55.1 §55.2 §55.6 §C.8 §E.1 §F.8 §I.5
- (2026k). Automated Researchers Can Mitigate Well-Characterized Alignment Failures. Anthropic Alignment Science Blog. non-peer-reviewed §55.1 §55.2 §55.3 §55.4 §55.6 §55.7 §55.8 §55.9 §55.10 §C.8 §E.3 §F.8
- (2026l). Automated researchers can reliably mitigate alignment failures. Anthropic. non-peer-reviewed §55.2 §55.4 §55.9 §C.8 §E.1 §F.8 §I.5
- (2026m). Automated Weak-to-Strong Researcher. Anthropic Alignment Science Blog. non-peer-reviewed §42.3 §42.8 Ch. 42 §55.2 Ch. 55 §C.8 §E.3 §F.8
- (2026n). Circuits Updates — June 2026. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2026o). Circuits Updates — May 2026. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2026p). Claude plays robotics. Anthropic. non-peer-reviewed §59.6 §59.8 §E.2 §F.9
- (2026q). Claude reveals ECDSA curve origins. Anthropic. non-peer-reviewed §E.2 §F.58
- (2026r). Claude's Constitution. Anthropic. non-peer-reviewed Ch. 19 §19.1 §19.2 §19.3 §19.4 §19.5 §19.6 §19.7 §19.9 Ch. 19 §20.2 §20.4 §20.5 §20.6 §20.8 §21.1 §21.5 §21.7 §23.1 §62.1 §70.3 §C.8 §F.13
- (2026s). Discovering cryptographic weaknesses with Claude. Anthropic. non-peer-reviewed §58.5 §E.2 §F.9
- (2026t). Donating our open-source alignment tool. Anthropic. non-peer-reviewed §E.1 §F.58
- (2026u). Evaluating and mitigating the growing risk of LLM-discovered 0-days. Anthropic. non-peer-reviewed §46.3 §46.4 §46.8 §46.9 §58.5 §58.8 §E.2 §F.9
- (2026v). Experimenting with AI to defend critical infrastructure. Anthropic. non-peer-reviewed §58.5 §E.2 §F.9
- (2026w). Fine-Tuned Lie Detectors Failed to Generalize. Anthropic Alignment Science Blog. non-peer-reviewed §39.1 §39.6 §39.7 §39.9 §39.11 §E.3 §F.6
- (2026x). GLM-5.3 and the spread of advanced cyber capabilities. Anthropic. non-peer-reviewed §58.5 §58.6 §58.10 §E.2 §F.9
- (2026y). Improving our alignment and security practices. Anthropic. non-peer-reviewed §54.1 §54.2 §54.3 §54.7 §F.13 §I.3
- (2026z). Investigating three incidents in our cybersecurity evaluations. Anthropic. non-peer-reviewed §54.4 §54.6 §54.7 §58.4 §C.8 §F.13 §I.3
- (2024). Foundational Challenges in Assuring Alignment and Safety of Large Language Models. arXiv. preprint §3.1 §71.1 §F.1
- (2024). We Need A ‘Science of Evals’. Apollo Research. non-peer-reviewed §5.1 §5.7 §36.2 §36.8 §F.6
- (2025). Claude Sonnet 3.7 (often) knows when it's in alignment evaluations. LessWrong. non-peer-reviewed §37.3 §37.10 §F.6 §H.2
- (1990). The Concept of Probability in Safety Assessments of Technological Systems. Science. §4.2 §F.51
- (2004). How Useful Is Quantitative Risk Assessment? Risk Analysis. §4.2 §52.4 §52.8 §F.51
- (2025). Chain-of-Thought Reasoning In The Wild Is Not Always Faithful. arXiv. preprint §40.3 §F.6
- (2024). Refusal in Language Models Is Mediated by a Single Direction. Advances in Neural Information Processing Systems. §46.2 §46.3 §46.8 §46.9 §48.2 §48.4 §48.8 §69.4 §F.8 §H.2
- (1978). Organizational learning. Addison-Wesley Pub. Co.. §53.4 §F.41
- (2017). Low Impact Artificial Intelligences. arXiv. preprint §F.24
- (2018). Occam's razor is insufficient to infer the preferences of irrational agents. Advances in Neural Information Processing Systems. §13.1 §13.4 §18.3 §22.1 §F.2
- (2017). Good and safe uses of AI Oracles. arXiv. preprint §28.5 §F.4
- (2017). 'Indifference' methods for managing agent rewards. arXiv. preprint §20.4 §F.24
- (2014). The errors, insights and lessons of famous AI predictions – and what they mean for the future. Journal of Experimental & Theoretical Artificial Intelligence. §2.2 §4.5 §F.28
- (2016). Racing to the precipice: a model of artificial intelligence development. AI & SOCIETY. §61.2 §65.2 §65.8 Ch. 65 §70.3 §C.3 §D.1 §F.29
- (2024). Training Language Models to Win Debates with Self-Play Improves Judge Accuracy. arXiv. preprint §41.5 §41.10 §70.3 §F.6
- (1969). A Ladder Of Citizen Participation. Journal of the American Institute of Planners. §17.7 §F.45
- (2019). A Ladder of Citizen Participation. Journal of the American Planning Association. §F.45
- (1963). Effect of the severity of threat on the devaluation of forbidden behavior. The Journal of Abnormal and Social Psychology. §25.2 §F.57
- (2016). Linear Algebraic Structure of Word Senses, with Applications to Polysemy. Transactions of the Association for Computational Linguistics. doi:10.1162/tacl_a_00034. §44.1 §F.7
- (2025). HealthBench: Evaluating Large Language Models Towards Improved Human Health. arXiv. preprint §F.6
- (2026). Language Model Circuits Are Sparse in the Neuron Basis. arXiv. preprint §45.5 §45.7 §45.8 §F.7
- (2015). Truth Is a Lie: Crowd Truth and the Seven Myths of Human Annotation. AI Magazine. §18.4 §18.10 Ch. 18 §22.7 §F.38 §H.3
- (1995). The Wassenaar Arrangement On Export Controls for Conventional Arms and Dual-Use Goods and Technologies. Wassenaar Arrangement Secretariat. non-peer-reviewed §64.7 §66.5 §F.30
- (1962). Economic Welfare and the Allocation of Resources for Invention. The Rate and Direction of Inventive Activity. §65.2 §F.25
- (1963). Uncertainty and the Welfare Economics of Medical Care. The American Economic Review. §61.1 §61.4 §F.46
- (2023). The feasibility of artificial consciousness through the lens of neuroscience. Trends in Neurosciences. §21.2 §F.44
- (2024). Situational Awareness: The Decade Ahead. situational-awareness.ai. non-peer-reviewed §2.6 §65.3 §65.5 §65.8 §C.6 §F.25
- (1956). An introduction to cybernetics. J. Wiley. §41.1 Ch. 41 §D.9 §F.21
- (1991). Requisite Variety and Its Implications for the Control of Complex Systems. Facets of Systems Science. §F.21
- (2019). The Role of Cooperation in Responsible AI Development. arXiv. preprint §64.3 §65.1 §65.2 §65.3 §65.4 §65.5 §65.6 §65.8 Ch. 65 §F.29
- (2021). A General Language Assistant as a Laboratory for Alignment. arXiv. preprint §1.1 §2.6 §3.3 Ch. 20 §20.1 §20.3 §20.6 Ch. 20 §23.1 §23.9 §C.5 §E.1 §F.4 §H.2
- (2026). TensorLens: End-to-End Transformer Analysis via High-Order Attention Tensors. Annual Meeting of the Association for Computational Linguistics. §F.2
- (2023a). Morality beyond the WEIRD: How the nomological network of morality varies across cultures. Journal of Personality and Social Psychology. §18.2 §F.38
- (2023b). Which Humans? Center for Open Science. preprint §17.4 §F.55
- (2018). Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples. International Conference on Machine Learning. §48.1 §48.9 §F.8 §H.2
- (1962). How to do things with words. Harvard University Press. §F.35
- (2021). Program Synthesis with Large Language Models. arXiv. preprint §F.2
- (2015). Why Are There Still So Many Jobs? The History and Future of Workplace Automation. Journal of Economic Perspectives. §68.5 §68.6 §F.25
- (1996). Compliance Quantified. Cambridge University Press. §14.6 §F.40
- (1996). Inspection games in arms control. European Journal of Operational Research. §F.40
- (2002). Chapter 51 Inspection games. Handbook of Game Theory with Economic Applications. §14.6 Ch. 14 §50.2 Ch. 50 §66.4 §66.9 Ch. 66 §C.1 §C.3 §D.6 §F.8
- (2018). The Mayhem Cyber Reasoning System. IEEE Security & Privacy. §58.5 §F.22
- (1985). The N-Version Approach to Fault-Tolerant Software. IEEE Transactions on Software Engineering. §50.4 §F.26
- (2018). The Moral Machine experiment. Nature. §F.47
- (1984). The evolution of cooperation. New York : Basic Books. §F.17
- (1981). The Evolution of Cooperation. Science. §57.2 §F.29
- (1985). Achieving Cooperation under Anarchy: Strategies and Institutions. World Politics. §65.6 §66.2 §F.32
- (2000). The base-rate fallacy and the difficulty of intrusion detection. ACM Transactions on Information and System Security. §6.7 §51.1 §54.2 Ch. 54 §58.2 §58.7 Ch. 58 §D.8 §F.22
- (2024). The Law of AI is the Law of Risky Agents without Intentions. Elsevier BV. preprint §63.4 §F.33
- (1992). Responsive Regulation. Oxford University PressNew York, NY. §62.5 §63.3 Ch. 63 §C.2 §D.3 §F.49
- (1989). Filling Gaps in Incomplete Contracts: An Economic Theory of Default Rules. The Yale Law Journal. §14.3 §19.2 Ch. 19 §F.33
- (2024). A General Theoretical Paradigm to Understand Learning from Human Preferences. Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (PMLR 238). §12.6 §22.4 §22.10 §F.2
- (2025). Recontextualization Mitigates Specification Gaming without Modifying the Specification. arXiv. preprint §24.5 §32.4 §33.1 §F.5
- (2023). The Internal State of an LLM Knows When It’s Lying. Findings of the Association for Computational Linguistics: EMNLP 2023. doi:10.18653/v1/2023.findings-emnlp.68. §39.1 §39.5 §39.6 §39.11 §F.6 §H.2
- (2021). T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based Text Classification. USENIX Security Symposium. §F.8
B
- (2016). Using Fast Weights to Attend to the Recent Past. Advances in Neural Information Processing Systems. §F.11
- (1985). Trading group theory for randomness. Proceedings of the seventeenth annual ACM symposium on Theory of computing - STOC '85. §41.3 §F.26
- (2019). Algorithms on regulatory lockdown in medicine. Science. §52.6 §54.5 §63.6 §F.36
- (2013). Expectations, outcomes, and challenges of modern code review. 2013 35th International Conference on Software Engineering (ICSE). §51.2 §51.6 §D.10 §F.50
- (2025). Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agents. arXiv. preprint §F.6
- (2003). Working memory: looking back and looking forward. Nature Reviews Neuroscience. §F.11
- (2022). If Influence Functions Are the Answer, Then What is the Question? Advances in Neural Information Processing Systems. doi:10.52202/068431-1305. §10.1 §F.2
- (2014). Neural Machine Translation by Jointly Learning to Align and Translate. International Conference on Learning Representations. §F.11
- (2022a). Constitutional AI: Harmlessness from AI Feedback. arXiv. preprint §2.6 §3.3 §3.8 §11.4 §22.7 §23.1 §23.2 §23.6 §23.9 Ch. 23 §C.5 §E.1 §E.3 §F.2
- (2022b). Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. arXiv. preprint §2.6 §3.3 §3.9 §12.2 §12.5 §18.5 §18.6 §18.10 §20.1 §20.6 §22.3 §22.5 §22.7 §C.5 §E.1 §E.3 §F.2 §H.2
- (2026). TASTE: Can AI Models Judge AI Safety Research Proposals? Anthropic Alignment Science Blog. non-peer-reviewed §55.3 §55.8 §55.9 §C.8 §E.3 §F.8 §I.4 §I.5
- (2024). Obfuscated Activations Bypass LLM Latent-Space Defenses. arXiv. preprint §39.8 §40.5 §46.4 §46.9 §47.7 §48.5 §48.6 §F.8 §H.2
- (1983). Ironies of automation. Automatica. §41.8 Ch. 41 §51.2 Ch. 51 §54.2 §60.4 §60.10 Ch. 60 §70.3 §C.2 §D.13 §F.31
- (1992). Incentive Contracts and Performance Measurement. Journal of Political Economy. §14.2 §F.25
- (2002). Distortion and Risk in Optimal Incentive Contracts. The Journal of Human Resources. §14.2 §F.25
- (2023). Nuclear Arms Control Verification and Lessons for AI Treaties. arXiv. preprint §66.3 §66.7 §66.9 §F.32
- (1994). Subjective Performance Measures in Optimal Incentive Contracts. The Quarterly Journal of Economics. §14.2 §F.25
- (2025). Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation. arXiv. preprint §1.7 §3.5 §4.7 §5.1 §5.7 Ch. 24 §24.4 §24.5 §24.9 Ch. 24 §30.1 §30.2 §30.3 §30.7 Ch. 30 §33.1 §40.1 §40.2 §40.4 §40.5 §40.6 §40.8 Ch. 40 §54.3 §69.5 §69.6 §70.3 §C.7 §F.8 §H.2
- (2026). Structural Inference: Interpreting Small Language Models with Susceptibilities. International Conference on Learning Representations. §10.2 §F.2
- (2013). What Drives Taxi Drivers? A Field Experiment on Fraud in a Market for Credence Goods. The Review of Economic Studies. §61.1 §61.8 §F.46
- (2025). Against willing servitude: Autonomy in the ethics of advanced artificial intelligence. The Philosophical Quarterly. §20.4 §21.7 §F.45
- (2024). Artificial Intelligence: Arguments for Catastrophic Risk. Philosophy Compass. §4.3 §F.42
- (2024a). Lessons from Studying Two-Hop Latent Reasoning. arXiv. preprint §37.1 §40.2 §40.8 §45.7 §52.5 §70.3 §F.8
- (2024b). Towards evaluations-based safety cases for AI scheming. arXiv. preprint §34.1 §34.8 §52.2 §52.5 §52.8 §F.8
- (2015). A prudent path forward for genomic engineering and germline gene modification. Science. §64.2 §F.43
- (2026). AI Integrity: Defending Against Backdoors and Secret Loyalties. arXiv. preprint §38.5 §51.1 §53.5 §68.3 §F.45
- (2021). Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. §60.5 §60.10 §F.31
- (2004). Multiscale variety in complex systems. Complexity. §F.21
- (2001). On the (Im)possibility of Obfuscating Programs. Lecture Notes in Computer Science. §28.6 §47.6 §F.7
- (2021). Representation Topology Divergence: A Method for Comparing Neural Network Representations. International Conference on Machine Learning. §F.7
- (2020). Debate update: Obfuscated arguments problem. AI Alignment Forum. non-peer-reviewed §3.5 §41.4 §41.10 Ch. 41 §70.3 §C.5 §F.14
- (2020). Writeup: Progress on AI Safety via Debate. AI Alignment Forum. non-peer-reviewed §41.4 §F.14
- (2002). When and where do we apply what we learn?: A taxonomy for far transfer. Psychological Bulletin. §26.6 §F.48
- (2023). Fairness and Machine Learning: Limitations and Opportunities. MIT Press. §F.55
- (2015). The Oracle Problem in Software Testing: A Survey. IEEE Transactions on Software Engineering. §24.2 §41.1 §F.50
- (2006). Can machine learning be secure? Proceedings of the 2006 ACM Symposium on Information, computer and communications security. §48.1 Ch. 48 §D.8 §F.22
- (2025). -Bench: Evaluating Conversational Agents in a Dual-Control Environment. arXiv. preprint §F.6
- (1994). Self-Enforcing International Environmental Agreements. Oxford Economic Papers. §66.2 §F.29
- (2010). By Parallel Reasoning. Oxford University Press. §69.1 §F.37
- (2020). Benign overfitting in linear regression. Proceedings of the National Academy of Sciences. doi:10.1073/pnas.1907378117. §9.2 §F.2
- (2024). Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies. International Conference on Machine Learning. §48.1 §F.8
- (2025). Generative AI without guardrails can harm learning: Evidence from high school mathematics. Proceedings of the National Academy of Sciences. §60.4 §60.5 §60.10 §F.31
- (2020). Influence Functions in Deep Learning Are Fragile. International Conference on Learning Representations. §10.1 §F.2
- (2006). Cues of being watched enhance cooperation in a real-world setting. Biology Letters. §37.5 §F.47
- (2017). Network Dissection: Quantifying Interpretability of Deep Visual Representations. Computer Vision and Pattern Recognition. doi:10.1109/CVPR.2017.354. §F.7
- (2026). SWE-chat: Coding Agent Interactions From Real Users in the Wild. arXiv. preprint §F.9
- (1995). Political Control Versus Expertise: Congressional Choices about Administrative Procedures. American Political Science Review. §19.6 §61.1 §D.4 §F.45
- (1998). Who Reviews the Reviewers? Feasibility of Using a Fictitious Manuscript to Evaluate Peer Reviewer Performance. Annals of Emergency Medicine. §55.3 §F.37
- (2016). The Implications of Modern Business–Entity Law for the Regulation of Autonomous Systems. European Journal of Risk Regulation. §21.6 §63.4 §F.33
- (2025). Measuring what Matters: Construct Validity in Large Language Model Benchmarks. Advances in Neural Information Processing Systems 38. §5.2 §36.4 §36.6 §36.7 §F.6
- (2020). An analysis and evaluation of methods currently used to quantify the likelihood of existential hazards. Futures. §4.5 §F.28
- (1994). Principles of biomedical ethics. New York : Oxford University Press. §16.5 §F.36
- (2019). Principles of Biomedical Ethics : Marking Its Fortieth Anniversary. The American Journal of Bioethics. §16.5 §F.36
- (2020). The Illusory Promise of Stakeholder Governance. Elsevier BV. preprint §53.6 §53.9 §61.5 §61.8 §62.6 §70.3 §F.49
- (1961). Boys in white: student culture in medical school. University of Chicago Press. §25.6 §F.57
- (2025). Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity. arXiv. preprint §60.1 §60.10 §F.9
- (2019). Abstracting Causal Models. Proceedings of the AAAI Conference on Artificial Intelligence. doi:10.1609/aaai.v33i01.33012678. §43.5 §F.7
- (1997). Weak Emergence. Noûs. §57.7 §F.21
- (1966). Ethics and Clinical Research. New England Journal of Medicine. §F.36
- (1984). The Viable System Model: Its Provenance, Development, Methodology and Pathology. Journal of the Operational Research Society. §F.21
- (2023). Approaching an unknown communication system by latent space exploration and causal inference. Royal Society Open Science. doi:10.1098/rsos.250829. §F.11
- (2025). Theoretical guarantees on the best-of-n alignment policy. International Conference on Machine Learning. §12.5 §12.9 §F.2
- (2003). Scope and Impact of Financial Conflicts of Interest in Biomedical Research. JAMA. §5.6 §F.37
- (2022). Probing Classifiers: Promises, Shortcomings, and Advances. Computational Linguistics. §3.6 §43.2 §43.8 §F.7
- (2019). Reconciling modern machine-learning practice and the classical bias–variance trade-off. Proceedings of the National Academy of Sciences. doi:10.1073/pnas.1903070116. §9.2 Ch. 9 §D.6 §F.2
- (1957). Dynamic Programming. Princeton University Press. §F.40
- (2024). Counting arguments provide no evidence for AI doom. AI Alignment Forum. non-peer-reviewed §3.4 §4.4 §4.7 §9.3 §33.1 §34.2 §34.10 Ch. 34 §35.3 §70.3 Ch. 70 §C.6 §F.14
- (2023a). Eliciting Latent Predictions from Transformers with the Tuned Lens. arXiv. preprint §43.2 §F.7
- (2023b). LEACE: Perfect linear concept erasure in closed form. Advances in Neural Information Processing Systems. §43.2 §46.2 §F.7
- (2024). Neural Networks Learn Statistics of Increasing Complexity. International Conference on Machine Learning. §9.3 §F.2
- (1972). Self-Perception Theory. Advances in Experimental Social Psychology. §69.4 §F.47
- (2012). Outsourcing Regulation: How Insurance Reduces Moral Hazard. Michigan Law Review. §63.5 Ch. 63 §D.5 §F.27
- (2014). More Than You Wanted to Know. Princeton University Press. §67.4 §67.8 §F.49
- (2003). The validity of psychophysiological detection of information with the Guilty Knowledge Test: A meta-analytic review. Journal of Applied Psychology. §39.4 §F.34
- (2003). Intrinsic and Extrinsic Motivation. Review of Economic Studies. §25.3 §F.25
- (2020). Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. §1.6 §11.7 §19.5 §D.18 §F.35
- (2021). On the Dangers of Stochastic Parrots. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. §1.6 §2.5 §C.5 §F.1
- (2017). The Consciousness Prior. arXiv. preprint §F.11
- (2012). Representation Learning: A Review and New Perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence. doi:10.1109/TPAMI.2013.50. §F.7
- (2024a). Can a Bayesian Oracle Prevent Harm from an Agent? arXiv. preprint §28.6 §52.4 §F.8
- (2024b). Managing extreme AI risks amid rapid progress. Science. §2.7 §61.6 §61.8 §66.1 §F.10
- (2025a). First Key Update: Capabilities and Risk Implications. International AI Safety Report (2025/033, DSIT). non-peer-reviewed §59.2 §F.9
- (2025b). International AI Safety Report. arXiv. preprint §1.1 §2.1 §2.2 §2.7 §2.10 §4.6 §58.1 §66.6 §C.2 §C.7 §F.9 §I.5
- (2025c). Second Key Update: Technical Safeguards and Risk Management. International AI Safety Report (2025/042, DSIT). non-peer-reviewed §48.5 §48.9 §52.1 §52.3 §52.4 §52.5 §52.6 §62.3 §62.5 §62.7 §62.9 §66.6 §F.8 §H.4 §I.5
- (2025d). Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path? arXiv. preprint §3.7 §3.8 §28.5 §28.9 §F.24
- (2025e). The Singapore Consensus on Global AI Safety Research Priorities. arXiv. preprint §2.7 §3.1 Ch. 3 §66.6 §71.1 Ch. 71 §C.7 §F.13
- (2026). International AI Safety Report 2026. International AI Safety Report. non-peer-reviewed §1.1 §2.7 §3.1 §4.1 §4.5 §4.6 §4.8 §58.1 §58.10 Ch. 58 §59.2 §59.7 §59.8 Ch. 59 §62.7 §63.2 §66.6 §66.9 Ch. 66 §C.8 §F.13 §H.2 §I.2 §I.5
- (2020). What is the point of fairness? ACM SIGACCESS Accessibility and Computing. §17.3 §20.3 §F.12
- (2016). Formalizing Convergent Instrumental Goals. AAAI 2016 AI, Ethics and Society Workshop. §35.1 §F.24
- (2023). Designing Fiduciary Artificial Intelligence. Equity and Access in Algorithms, Mechanisms, and Optimization. §56.8 §F.33
- (2024). Sabotage Evaluations for Frontier Models. arXiv. preprint §3.7 §34.5 §50.3 §51.4 §55.5 Ch. 55 §56.3 §C.6 §E.1 §E.3 §F.8
- (2026). Terminal Wrench: A Dataset of 331 Reward-Hackable Environments and 3,632 Exploit Trajectories. arXiv. preprint §F.9
- (2024). Mechanistic Interpretability for AI Safety – A Review. Trans. Mach. Learn. Res.. §F.7
- (1974). Potential Biohazards of Recombinant DNA Molecules. Science. §2.7 §59.5 §64.2 §C.2 §F.30
- (1975). Summary statement of the Asilomar conference on recombinant DNA molecules. Proceedings of the National Academy of Sciences. §2.7 §59.5 §62.5 §64.2 §64.8 §64.10 Ch. 64 §C.2 §D.16 §F.30
- (2023a). Taken out of context: On measuring situational awareness in LLMs. arXiv. preprint §3.4 §11.3 §26.3 §27.4 §34.1 §37.1 §C.6 §F.5
- (2023b). The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A". International Conference on Learning Representations. §F.11
- (2024). STELA: a community-centred approach to norm elicitation for AI alignment. Scientific Reports. §13.5 §17.7 §F.55
- (2017). Safe Model-based Reinforcement Learning with Stability Guarantees. Advances in Neural Information Processing Systems. §28.6 §28.9 §D.9 §F.4
- (1958). Two Concepts of Liberty. Clarendon Press. §F.42
- (2009). Beyond Revealed Preference: Choice-Theoretic Foundations for Behavioral Welfare Economics *. Quarterly Journal of Economics. §13.1 §13.6 §F.25
- (1986a). Common Agency. Econometrica. §1.4 §14.4 §61.3 §C.2 §D.1 §F.25
- (2012). The Transparency Paradox. Administrative Science Quarterly. §25.2 §34.6 §37.5 §F.54
- (1998). What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience? Brain Research Reviews. §29.4 §29.5 §29.9 Ch. 29 §D.15 §F.39
- (2025). The Validation Gap: A Mechanistic Analysis of How Language Models Compute Arithmetic but Fail to Validate It. Conference on Empirical Methods in Natural Language Processing. §F.7
- (2005). Competition and Incentives with Motivated Agents. American Economic Review. §14.5 §14.8 §61.3 §65.4 §F.25
- (2025a). Tell me about yourself: LLMs are aware of their learned behaviors. International Conference on Learning Representations. §26.3 §26.4 §26.7 §26.8 §26.9 Ch. 26 §32.2 §37.1 §39.9 §F.5
- (2025b). Weird Generalization and Inductive Backdoors: New Ways to Corrupt LLMs. arXiv. preprint §27.5 §32.2 §32.5 §32.7 §32.9 §48.6 §F.8
- (2026a). Training large language models on narrow tasks can lead to broad misalignment. Nature. §1.7 §3.4 §5.7 §11.6 §26.3 §26.4 §26.9 Ch. 26 §31.7 §32.1 §32.2 §32.5 §32.6 §32.8 §32.9 Ch. 32 §69.4 §C.7 §F.5 §H.2
- (2026b). Value Leakage: An LLM's Answers Are Silently Shaped by Its Own Values. arXiv. preprint §18.8 §18.10 §26.5 §F.4
- (2025). Design Patterns for Securing LLM Agents against Prompt Injections. arXiv. preprint §28.5 §49.6 §F.8
- (2024). Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning. arXiv. preprint §F.8
- (2006). What’s Measured Is What Matters: Targets and Gaming in the English Public Health Care System. Public Administration. §15.2 §53.9 §F.41 §H.3
- (2023). Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment. arXiv. preprint §55.3 §55.9 §D.20 §F.37 §H.3
- (2024). Finding Transformer Circuits with Edge Pruning. Advances in Neural Information Processing Systems. §45.3 §45.6 §F.7
- (2025). Ctrl-Z: Controlling AI Agents via Resampling. arXiv. preprint §1.3 §3.7 §3.9 §14.8 §50.3 §50.6 §69.2 §F.8
- (2020). From ethics washing to ethics bashing. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency. §61.4 §F.12
- (2025). Finance Agent Benchmark: Benchmarking LLMs on Real-world Financial Research Tasks. arXiv. preprint §F.6
- (2018). Wild patterns: Ten years after the rise of adversarial machine learning. Pattern Recognition. §48.1 §F.8
- (2012). Poisoning Attacks against Support Vector Machines. arXiv. preprint §48.1 §F.8
- (2024). Looking Inward: Language Models Can Learn About Themselves by Introspection. arXiv. preprint §21.5 §21.9 §46.7 §F.7
- (2024). Hopping Too Late: Exploring the Limitations of Large Language Models on Multi-Hop Queries. Conference on Empirical Methods in Natural Language Processing. §F.2
- (2017). Animal sentience and the precautionary principle. Animal Sentience. §21.6 §64.8 §F.44
- (2024). The Edge of Sentience. Oxford University PressOxford. §21.1 §21.2 §21.3 §21.4 §21.6 §21.8 §21.9 Ch. 21 §70.3 §F.44 §H.3
- (2021). Algorithmic injustice: a relational ethics approach. Patterns. §13.5 §F.20
- (2022a). Power to the People? Opportunities and Challenges for Participatory AI. Equity and Access in Algorithms Mechanisms and Optimization. §17.7 §F.45
- (2022b). The Values Encoded in Machine Learning Research. 2022 ACM Conference on Fairness Accountability and Transparency. §2.1 §F.12
- (2024). AI auditing: The Broken Bus on the Road to AI Accountability. 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML). §38.6 §67.2 §F.10
- (2006). Pattern Recognition and Machine Learning. New York : Springer. §F.56
- (2008). Defining the insider threat. Proceedings of the 4th annual workshop on Cyber security and information intelligence research: developing strategies to meet the cyber security and information intelligence challenges ahead. §50.1 §53.5 §56.7 §D.8 §F.22
- (1948). On the Rationale of Group Decision-making. Journal of Political Economy. §F.52
- (2001). Decentring Regulation: Understanding the Role of Regulation and Self-Regulation in a 'Post-Regulatory' World. Current Legal Problems. §63.3 §F.49
- (2010). Really Responsive Risk-Based Regulation. Law & Policy. §63.3 §F.49
- (2025). RepliBench: Evaluating the Autonomous Replication Capabilities of Language Model Agents. arXiv. preprint §35.6 §35.7 §35.8 §36.1 §36.10 §70.1 §F.5
- (2020). What is the State of Neural Network Pruning? Conference on Machine Learning and Systems. §F.2
- (1980). Bridging moral cognition and moral action: A critical review of the literature. Psychological Bulletin. §25.4 §D.11 §F.57
- (1955). The dynamics of bureaucracy: a study of interpersonal relations in two government agencies. University of Chicago Press. §15.2 §F.41
- (1995). On a confusion about a function of consciousness. Behavioral and Brain Sciences. §21.1 §F.3
- (2009). Safety and Assurance Cases: Past, Present and Possible Future – an Adelard Perspective. Making Systems Safer. §52.1 §52.2 §D.7 §F.51
- (2024). AI and biosecurity: The need for governance. Science. §59.4 §59.5 Ch. 59 §63.7 §F.18
- (2008). Gradient Pursuits. IEEE Transactions on Signal Processing. §F.11
- (2011). Supervisory Letter SR 11-7 on guidance on Model Risk Management. Board of Governors of the Federal Reserve System. non-peer-reviewed §38.6 Ch. 38 §64.6 §67.3 §C.3 §D.5 §F.27
- (2026). Supervisory Letter SR 26-2 on Revised Guidance on Model Risk Management. Board of Governors of the Federal Reserve System. non-peer-reviewed §38.6 §64.6 §67.3 §F.27
- (2026). Slot Machines: How LLMs Keep Track of Multiple Entities. arXiv. preprint §F.11
- (2017). Implementation of Moral Uncertainty in Intelligent Machines. Minds and Machines. §F.42
- (2021). An Interpretability Illusion for BERT. arXiv. preprint §F.7
- (2023). The Foundation Model Transparency Index. arXiv. preprint §67.4 §67.8 §F.13
- (2024). Considerations for governing open foundation models. Science. §59.4 §63.7 §67.6 §F.45
- (2006). Accuracy of Deception Judgments. Personality and Social Psychology Review. §39.3 §39.11 Ch. 39 §69.3 §D.11 §F.34 §H.3
- (2025). Demonstrating specification gaming in reasoning models. arXiv. preprint §30.1 §30.7 §56.3 §70.3 §F.9 §H.2
- (2021). Improving language models by retrieving from trillions of tokens. International Conference on Machine Learning. §F.2
- (2010). A Reliability-Generalization Study of Journal Peer Reviews: A Multilevel Meta-Analysis of Inter-Rater Reliability and Its Determinants. PLoS ONE. §5.7 §55.3 §F.37
- (2004). The Concept of Validity. Psychological Review. §F.48
- (2022). Petals: Collaborative Inference and Fine-tuning of Large Models. Annual Meeting of the Association for Computational Linguistics. §F.4
- (2012). The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents. Minds and Machines. §2.3 §2.9 §4.3 §16.1 §16.11 §35.1 §35.7 Ch. 35 §C.3 §F.42
- (2014). Superintelligence: Paths, Dangers, Strategies. TEELL. §2.3 Ch. 2 §C.3 §F.42
- (2017). Strategic Implications of Openness in AI Development. Global Policy. §3.8 §63.7 §65.2 §65.5 §F.29
- (2019). The Vulnerable World Hypothesis. Global Policy. §4.2 §F.25
- (2014). What do philosophers believe? Philosophical Studies. §F.42
- (2023). Philosophers on Philosophy: The 2020 PhilPapers Survey. Philosophers' Imprint. §F.42
- (2021). Machine Unlearning. 2021 IEEE Symposium on Security and Privacy (SP). §27.7 §F.4
- (2002). From Street‐Level to System‐Level Bureaucracies: How Information and Communication Technology is Transforming Administrative Discretion and Constitutional Control. Public Administration Review. §19.6 §F.46
- (2025). Scaling Trends for Data Poisoning in LLMs. Proceedings of the AAAI Conference on Artificial Intelligence. §27.6 §48.6 §F.8
- (2026). Automated alignment is harder than you think. arXiv. preprint Ch. 55 §55.1 §55.4 §55.6 §55.8 §55.9 Ch. 55 §70.3 §C.8 §F.8
- (2022). Settling the Reward Hypothesis. arXiv. preprint §7.2 §7.5 Ch. 7 §C.1 §D.6 §F.24
- (2025). Putting up Bumpers. Anthropic Alignment Science Blog. non-peer-reviewed §3.8 §3.9 §71.5 §E.3 §F.1 §I.5
- (2021). What Will it Take to Fix Benchmarking in Natural Language Understanding? Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. §36.4 §F.6
- (2015). A large annotated corpus for learning natural language inference. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/D15-1075. §F.11
- (2022). Measuring Progress on Scalable Oversight for Large Language Models. arXiv. preprint §3.5 §41.1 §41.10 §41.11 §E.1 §E.3 §F.6
- (2025). Anthropic's Pilot Sabotage Risk Report. Anthropic Alignment Science Blog. non-peer-reviewed §52.4 §52.8 §62.7 §C.7 §E.3 §F.8 §I.2
- (1985). Culture and the Evolutionary Process. University of Chicago Press. §57.6 §F.17
- (2020). The Brussels Effect. Oxford University PressNew York. §63.3 §66.7 §F.49
- (1952). Rank Analysis of Incomplete Block Designs: I. The Method of Paired Comparisons. Biometrika. §13.2 §F.56
- (1982). Enforced Self-Regulation: A New Strategy for Corporate Crime Control. Michigan Law Review. §62.5 Ch. 62 §D.3 §F.49
- (2016). Introduction to Computational Social Choice. Handbook of Computational Social Choice. §F.42
- (1987). Intention, Plans, and Practical Reason. Harvard University Press. §1.1 §F.42
- (2025). Interpretability in Parameter Space: Minimizing Mechanistic Description Length with Attribution-based Parameter Decomposition. arXiv. preprint §43.7 §45.6 §45.8 §F.7
- (1997). Working, Shirking, and Sabotage. University of Michigan Press. §25.7 §34.6 §51.3 §F.46
- (1961). The misbehavior of organisms. American Psychologist. §9.3 §25.5 §25.9 Ch. 25 §C.1 §D.14 §F.15
- (2023). Towards Monosemanticity: Decomposing Language Models With Dictionary Learning. Transformer Circuits Thread. non-peer-reviewed §3.6 §3.8 §3.9 §5.7 §44.1 §44.3 §44.5 §44.6 §44.8 Ch. 44 §E.4 §F.7 §H.2
- (1950). Verification of Forecasts Expressed in Terms of Probability. Monthly Weather Review. §4.5 §6.4 Ch. 6 §D.7 §F.28
- (2023). Machine culture. Nature Human Behaviour. §57.6 §F.17
- (2024). A Mechanistic Analysis of a Transformer Trained on a Symbolic Multi-Step Reasoning Task. Annual Meeting of the Association for Computational Linguistics. §F.7
- (2025). Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languages. North American Chapter of the Association for Computational Linguistics. §F.7
- (1986). Indicators of poor welfare. British Veterinary Journal. §21.4 §F.16
- (1968). Auto‐shaping of the Pigeon's Key‐peck 1. Journal of the Experimental Analysis of Behavior. §25.5 §25.9 §29.5 §29.9 §33.2 §D.14 §F.15 §H.3
- (2020). Language Models are Few-Shot Learners. Advances in Neural Information Processing Systems. §2.4 §11.1 §F.2
- (2024). Large Language Monkeys: Scaling Inference Compute with Repeated Sampling. arXiv. preprint §F.11
- (2024). Scalable AI Safety via Doubly-Efficient Debate. International Conference on Machine Learning. §3.5 §41.3 §41.4 §41.10 §69.3 §F.6 §H.1
- (2025). Avoiding Obfuscation with Prover-Estimator Debate. arXiv. preprint §3.5 §41.4 §41.10 Ch. 41 §F.6
- (2022). Assessing measures of animal welfare. Biology & Philosophy. §21.4 §F.16
- (2022). Animal sentience. Philosophy Compass. §21.1 §F.16
- (2018). The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation. arXiv. preprint §4.1 §F.13
- (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. arXiv. preprint §3.7 §67.1 §67.6 §F.13
- (2019). On Identifiability in Transformers. International Conference on Learning Representations. §F.2
- (2022). The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence. Daedalus. §60.6 §68.3 §68.5 §F.25
- (2025). Generative AI at Work. The Quarterly Journal of Economics. §68.5 §68.8 §F.25
- (2010). Robots should be slaves. Natural Language Processing. §21.6 §21.9 §F.44
- (2017). Of, for, and by the people: the legal lacuna of synthetic persons. Artificial Intelligence and Law. §21.6 §63.4 §F.33
- (2013). Climate change prediction: Erring on the side of least drama? Global Environmental Change. §4.6 §70.1 §F.28
- (2013). Risk and Rationality. Oxford University Press. §7.2 §F.24
- (2017). The Cybersecurity Dilemma. Oxford University Press. §58.8 §65.3 §F.32
- (1990). Deciding for Others. Cambridge University Press. §16.6 §F.36
- (2006). The Legitimacy of Global Governance Institutions. Ethics & International Affairs. §17.5 §66.1 §F.45
- (2021). To Trust or to Think. Proceedings of the ACM on Human-Computer Interaction. §60.5 §F.31
- (2025). Position: Ensuring mutual privacy is necessary for effective external evaluation of proprietary AI systems. arXiv. preprint §38.8 §66.4 §67.6 §71.6 §F.10
- (2013). Morgan’s Canon, meet Hume’s Dictum: avoiding anthropofabulation in cross-species comparisons. Biology & Philosophy. §5.4 §21.3 §31.4 §34.7 §37.6 §D.14 §F.15
- (2009). Improving Communication of Uncertainty in the Reports of the Intergovernmental Panel on Climate Change. Psychological Science. §4.6 §70.1 §F.28
- (2025). Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a multicentre, observational study. The Lancet Gastroenterology & Hepatology. §60.4 §60.10 §F.31
- (2003). The Logic of Political Survival. The MIT Press. §68.2 §68.8 §F.45
- (2024). Safety cases for frontier AI. arXiv. preprint §52.1 §52.2 §52.5 §52.8 §D.7 §F.51
- (2025). An alignment safety case sketch based on debate. arXiv. preprint §41.5 §52.3 §52.5 §52.8 §55.6 §55.9 §55.10 §F.8
- (2019). Artificial Intelligence, Discretion, and Bureaucracy. The American Review of Public Administration. §19.6 §F.46
- (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings of the 1st Conference on Fairness, Accountability and Transparency, PMLR 81:77-91. §2.5 §38.6 §C.4 §F.55
- (1979). Manufacturing Consent. University of Chicago Press. §34.6 §F.54
- (2022). Implementation of Additional Export Controls: Certain Advanced Computing and Semiconductor Manufacturing Items; Supercomputer and Semiconductor End Use; Entity List Modification. Federal Register, 87 FR 62186 (rule). non-peer-reviewed §65.1 §66.5 §F.13
- (2025). Framework for Artificial Intelligence Diffusion. Federal Register, 90 FR 4544 (interim final rule). non-peer-reviewed §65.1 §66.5 §F.13
- (2024). Truth is Universal: Robust Detection of Lies in LLMs. Advances in Neural Information Processing Systems. §39.1 §39.5 §39.6 §39.7 §39.11 §F.6 §H.2
- (1774). Speech to the Electors of Bristol. The Founders' Constitution, University of Chicago Press (vol. 1, ch. 13, doc. 7). non-peer-reviewed §1.2 §F.45
- (2023). Rethink reporting of evaluation results in AI. Science. §36.7 §F.6
- (2022). Discovering Latent Knowledge in Language Models Without Supervision. International Conference on Learning Representations. §3.5 §39.7 Ch. 39 §42.5 §C.5 §F.6
- (2024). Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision. International Conference on Machine Learning. §3.5 Ch. 42 §42.1 §42.2 §42.3 §42.4 §42.6 §42.7 §42.8 Ch. 42 §70.3 §C.6 §F.6 §H.2
- (2006). Genes in Conflict. Harvard University Press. §29.7 §F.17
- (2020). Mind the gaps: Assuring the safety of autonomous systems from an engineering, ethical, and legal perspective. Artificial Intelligence. §52.2 §F.51
- (2024a). The Local Interaction Basis: Identifying Computationally-Relevant and Sparsely Interacting Features in Neural Networks. arXiv. preprint §45.6 §F.7
- (2024b). Using Degeneracy in the Loss Landscape for Mechanistic Interpretability. arXiv. preprint §F.7
- (2025). Stochastic Parameter Decomposition. arXiv. preprint §43.7 §45.6 §45.8 §F.7
- (2024). BatchTopK Sparse Autoencoders. arXiv. preprint §44.5 §F.7
- (1993). The infeasibility of quantifying the reliability of life-critical real-time software. IEEE Transactions on Software Engineering. §6.5 §6.7 §52.1 §52.8 §D.8 §F.8 §H.3
- (2024). Reinforcement learning and artificial agency. Mind & Language. §7.1 §F.42
- (2025). Principles for Responsible AI Consciousness Research. Journal of Artificial Intelligence Research. §21.6 §F.44
- (2023). Consciousness in Artificial Intelligence: Insights from the Science of Consciousness. arXiv. preprint Ch. 21 §21.1 §21.2 §21.3 §21.6 §21.9 Ch. 21 §70.3 §D.15 §F.44 §H.3
- (2025). “Sharp Left Turn” discourse: An opinionated review. AI Alignment Forum. non-peer-reviewed §29.1 §29.2 §31.7 §F.14
C
- (2023). Toward a Perspectivist Turn in Ground Truthing for Predictive Computing. Proceedings of the AAAI Conference on Artificial Intelligence. §18.4 §F.38
- (1970). The costs of accidents: a legal and economic analysis. Yale University Press. §63.1 §F.33
- (2020). Artificial Intelligence, Algorithmic Pricing, and Collusion. American Economic Review. §57.3 §57.7 §57.9 §70.1 §F.9
- (2013). Preventing Regulatory Capture. Cambridge University Press. §61.6 §63.3 §F.49
- (1994). Reinforcement, Reward, and Intrinsic Motivation: A Meta-Analysis. Review of Educational Research. §25.3 §25.9 §25.10 §33.2 §69.3 §F.57 §H.3
- (2001). Pervasive negative effects of rewards on intrinsic motivation: The myth continues. The Behavior Analyst. §F.47
- (2020). Curve Detectors. Distill. §F.7
- (1979). Assessing the impact of planned social change. Evaluation and Program Planning. §15.1 §C.2 §D.20 §F.25
- (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin. §5.2 §F.48
- (2025). A Frontier AI Risk Management Framework: Bridging the Gap Between Current AI Practices and Established Risk Management. arXiv. preprint §62.3 §F.13
- (2001). Leadership and Pandering: A Theory of Executive Policymaking. American Journal of Political Science. §20.1 §F.45
- (2015). Towards Making Systems Forget with Machine Unlearning. 2015 IEEE Symposium on Security and Privacy. §27.7 §F.4
- (2021a). Identifiability in inverse reinforcement learning. Advances in Neural Information Processing Systems. §13.4 §22.1 §F.2
- (2021b). Low-Complexity Probing via Finding Subnetworks. North American Chapter of the Association for Computational Linguistics. doi:10.18653/V1/2021.NAACL-MAIN.74. §F.7
- (1971). Competitive Bidding in High-Risk Situations. Journal of Petroleum Technology. §7.7 §F.40
- (2012). The CERT guide to insider threats: how to prevent, detect, and respond to information technology crimes (theft, sabotage, fraud). Upper Saddle River, NJ : Addison-Wesley. §51.1 §53.5 §56.7 §D.8 §F.22
- (2026). Alignment as Jurisprudence. arXiv. preprint §19.4 §23.3 §D.3 §F.33
- (2018). Incorrigibility in the CIRL Framework. Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society. §20.4 §20.8 §22.2 §22.10 §35.5 §70.3 §F.24 §H.1
- (2023). Human Control: Definitions and Algorithms. Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (PMLR 216). §3.2 §20.4 §F.1
- (2025). Incentives for responsiveness, instrumental control and impact. Artificial Intelligence. doi:10.1016/j.artint.2025.104408. §14.7 §14.9 §F.2
- (2017a). Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods. AISec@CCS. doi:10.1145/3128572.3140444. §F.8
- (2017b). Towards Evaluating the Robustness of Neural Networks. 2017 IEEE Symposium on Security and Privacy (SP). §48.1 §F.8
- (2019). On Evaluating Adversarial Robustness. arXiv. preprint §48.1 §F.8
- (2020). Extracting Training Data from Large Language Models. USENIX Security Symposium. §F.2
- (2023). Are aligned neural networks adversarially aligned? Advances in Neural Information Processing Systems. §F.8
- (2024). Poisoning Web-Scale Training Datasets is Practical. 2024 IEEE Symposium on Security and Privacy (SP). §27.6 §48.6 §F.8
- (2025). LLMs unlock new paths to monetizing exploits. arXiv. preprint §F.9
- (2022). Is Power-Seeking AI an Existential Risk? arXiv. preprint §4.3 §4.4 §4.9 Ch. 4 §35.1 Ch. 35 §C.5 §F.42 §I.3
- (2023). Scheming AIs: Will AIs fake alignment during training in order to get power? arXiv. preprint §3.4 §4.7 §9.3 §11.7 §33.1 Ch. 33 §34.1 §34.2 §34.3 §34.5 §34.10 Ch. 34 §70.3 §C.6 §F.5
- (2025). Can we safely automate alignment research? Joe Carlsmith. non-peer-reviewed §55.1 §F.14
- (1999). Highly optimized tolerance: A mechanism for power laws in designed systems. Physical Review E. §4.2 §28.6 §F.21
- (2002). The Forging of Bureaucratic Autonomy. Princeton University Press. §61.6 §F.45
- (2014). Reputation and Power. Princeton University Press. §52.6 §63.6 §64.1 §64.5 §64.10 §D.17 §F.45
- (2015). Robustness and Linear Contracts. American Economic Review. §14.1 §F.25
- (2019). On the Utility of Learning about Humans for Human-AI Coordination. Advances in Neural Information Processing Systems. §22.2 §57.5 §F.9
- (2020). The CARE Principles for Indigenous Data Governance. Data Science Journal. §17.4 §27.3 Ch. 27 §F.12
- (2021). Operationalizing the CARE and FAIR Principles for Indigenous data futures. Scientific Data. §27.3 §F.12
- (2022). Estimating and Penalizing Induced Preference Shifts in Recommender Systems. International Conference on Machine Learning. §1.7 §13.6 §22.6 §60.2 §69.6 §F.42
- (2023). Characterizing Manipulation from AI Systems. Equity and Access in Algorithms, Mechanisms, and Optimization. §14.7 §16.9 §60.2 §60.6 Ch. 60 §F.42
- (2024). AI Alignment with Changing and Influenceable Reward Functions. International Conference on Machine Learning. §16.2 §16.9 §16.11 §22.6 §60.2 §70.3 §F.9
- (2026). Investigating the consequences of accidentally grading CoT during RL. OpenAI Alignment Research Blog. non-peer-reviewed §40.5 §40.8 §54.3 §E.5 §F.8
- (2017). Using Artificial Intelligence to Augment Human Intelligence. Distill. §28.7 §28.9 §F.43
- (2023). The Convergence of Artificial Intelligence and the Life Sciences: Safeguarding Technology, Rethinking Governance, and Preventing Catastrophe. Nuclear Threat Initiative. non-peer-reviewed §59.5 §F.18
- (2012). Evidence-Based Policy. Oxford University Press. §69.1 §F.37
- (2025). Steering Out-of-Distribution Generalization with Concept Ablation Fine-Tuning. arXiv. preprint §26.3 §32.1 §32.3 §32.9 §F.5 §H.2
- (2015). The Death of Rules and Standards. Elsevier BV. preprint §F.33
- (2014). The Retention of Manual Flying Skills in the Automated Cockpit. Human Factors: The Journal of the Human Factors and Ergonomics Society. §60.4 §60.10 §F.31
- (2023). Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. arXiv. preprint §3.3 §15.6 Ch. 22 §22.6 §22.8 Ch. 22 §71.1 Ch. 71 §F.2
- (2024a). Black-Box Access is Insufficient for Rigorous AI Audits. The 2024 ACM Conference on Fairness, Accountability, and Transparency. §1.7 §38.1 §38.8 §43.7 §47.7 §63.7 §67.6 §71.6 §F.7
- (2024b). Defending Against Unforeseen Failure Modes with Latent Adversarial Training. Trans. Mach. Learn. Res.. §F.8
- (2011). Peto's Paradox: evolution's prescription for cancer prevention. Trends in Ecology & Evolution. §F.17
- (2019). Hopes and fears for intelligent machines in fiction and reality. Nature Machine Intelligence. §2.8 §F.30
- (2018). An AI Race for Strategic Advantage. Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society. §65.1 §65.5 §65.8 §70.3 §F.25
- (2020). AI Narratives. Oxford University PressOxford. §2.8 §2.10 §F.30
- (2025). What will society think about AI consciousness? Lessons from the animal case. Trends in Cognitive Sciences. §21.1 §F.44
- (2010). On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation. Journal of Machine Learning Research. §7.7 §15.3 §F.40
- (2023). Statement on AI Risk. Center for AI Safety. non-peer-reviewed §2.7 §64.8 §F.13
- (2026). CAISI's Assessment of Z.ai's GLM-5.3 Cyber Capabilities. NIST. non-peer-reviewed §58.6 §58.10 §63.2 §63.7 §63.9 §F.13
- (2007). Adaptive Multilevel Splitting for Rare Event Analysis. Stochastic Analysis and Applications. §6.6 §F.2
- (2024). MaxMin-RLHF: Alignment with Diverse Human Preferences. arXiv. preprint §17.2 §17.8 §22.7 §F.42
- (2023). Could a Large Language Model be Conscious? Boston Review, August 9, 2023. §21.2 §F.3
- (2022). Shard Theory in Nine Theses: a Distillation and Critical Appraisal. AI Alignment Forum. non-peer-reviewed §33.1 §F.14
- (2015). Listen, Attend and Spell. IEEE International Conference on Acoustics, Speech, and Signal Processing. doi:10.1109/ICASSP.2016.7472621. §F.11
- (2019). The Assistive Multi-Armed Bandit. 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI). §22.2 §F.4
- (2022). Causal Scrubbing: a method for rigorously testing interpretability hypotheses. AI Alignment Forum. non-peer-reviewed §F.7
- (2023). Natural Abstractions: Key Claims, Theorems, and Critiques. AI Alignment Forum. non-peer-reviewed §46.6 §46.9 §F.14
- (2024). Visibility into AI Agents. Conference on Fairness, Accountability and Transparency. doi:10.1145/3630106.3658948. §11.5 §56.1 §F.9
- (2025). Infrastructure for AI Agents. arXiv. preprint §49.8 §63.3 §F.8
- (2014). Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers. Behavior Research Methods. §37.5 §69.4 §F.47
- (1981). Alternation. Journal of the ACM. §41.3 §F.6
- (1997). Incommensurability, Incomparability, and Practical Reason. Harvard University Press. §13.6 §F.42
- (2024). Language Models Need Inductive Biases to Count Inductively. International Conference on Learning Representations. §F.2
- (2022). The Geometry of Multilingual Language Model Representations. Conference on Empirical Methods in Natural Language Processing. §F.7
- (2024). A is for Absorption: Studying Feature Splitting and Absorption in Sparse Autoencoders. Neural Information Processing Systems. §44.6 §44.8 Ch. 44 §69.4 §F.7 §H.2
- (2023). Jailbreaking Black Box Large Language Models in Twenty Queries. 2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML). doi:10.1109/SaTML64287.2025.00010. §F.8
- (2025). Text-to-LoRA: Instant Transformer Adaption. International Conference on Machine Learning. §F.2
- (2026). Doc-to-LoRA: Learning to Instantly Internalize Contexts. arXiv. preprint §F.11
- (2024). Quantifying the Gain in Weak-to-Strong Generalization. Advances in Neural Information Processing Systems. doi:10.52202/079017-4017. §42.2 §42.8 §42.9 §F.6 §H.1 §H.2
- (2024). Evaluating Open-Source Sparse Autoencoders on Disentangling Factual Knowledge in GPT-2 Small. arXiv. preprint §F.7
- (2025). Evaluation Awareness Scales Predictably in Open-Weights Large Language Models. arXiv. preprint §37.3 §37.10 §70.3 §F.6 §H.2
- (1993). On compliance. International Organization. §66.2 §F.32
- (2025). Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities. arXiv. preprint §48.4 §F.8
- (2017). Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning. arXiv. preprint §48.6 §F.8
- (2019). Metamorphic Testing. ACM Computing Surveys. §24.2 §D.10 §F.50
- (2021). Evaluating Large Language Models Trained on Code. arXiv. preprint §F.6
- (2023a). Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations. International Conference on Machine Learning. §F.11
- (2023b). Dynamical versus Bayesian Phase Transitions in a Toy Model of Superposition. arXiv. preprint §10.2 §44.3 §44.8 §F.2 §H.2
- (2023c). The emergence of economic rationality of GPT. Proceedings of the National Academy of Sciences. §1.5 §7.3 §F.25
- (2024a). Designing a Dashboard for Transparency and Control of Conversational AI. arXiv. preprint §F.8
- (2024b). From Persona to Personalization: A Survey on Role-Playing Language Agents. Trans. Mach. Learn. Res.. §F.4
- (2024c). SelfIE: Self-Interpretation of Large Language Model Embeddings. International Conference on Machine Learning. §F.2
- (2024d). Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning. International Conference on Computational Linguistics. §F.4
- (2025a). Evaluating o1-Like LLMs: Unlocking Reasoning for Translation through Comprehensive Analysis. arXiv. preprint §F.6
- (2025b). Meta-SecAlign: Training LLMs against Prompt Injection for Robust Agents. arXiv. preprint §49.5 §F.8
- (2025c). Persona Vectors: Monitoring and Controlling Character Traits in Language Models. arXiv. preprint §11.6 §26.2 §26.3 §26.9 §32.3 §32.6 §32.9 §46.4 §46.5 §46.9 §F.5
- (2025d). Reasoning Models Don't Always Say What They Think. arXiv. preprint §40.3 §40.4 §40.8 Ch. 40 §E.1 §E.3 §F.6 §H.2
- (2025e). SecAlign: Defending Against Prompt Injection with Preference Optimization. Proceedings of the 2025 ACM SIGSAC Conference on Computer and Communications Security. §49.5 §F.8
- (2025f). StruQ: Defending Against Prompt Injection with Structured Queries. 34th USENIX Security Symposium (USENIX Security 25). §49.5 §F.8
- (2023). Backdoor Attacks and Countermeasures in Natural Language Processing Models: A Comprehensive Security Review. IEEE Transactions on Neural Networks and Learning Systems. doi:10.1109/TNNLS.2025.3540303. §F.8
- (2024). Can AI Assistants Know What They Don't Know? arXiv. preprint §F.11
- (2024). Llama Guard 3 Vision: Safeguarding Human-AI Image Understanding Conversations. arXiv. preprint §F.11
- (2023). Identifying and Adapting Transformer-Components Responsible for Gender Bias in an English Language Model. BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP. §F.2
- (2011). A Legal Theory for Autonomous Artificial Agents. University of Michigan Press. §56.8 §F.33
- (2017). Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments. Big Data. §2.5 §17.3 §17.8 Ch. 17 §C.4 §F.55 §H.1
- (2025). Identifying Sparsely Active Circuits Through Local Loss Landscape Decomposition. arXiv. preprint §45.6 §F.7
- (2025). Decomposition of Small Transformer Models. arXiv. preprint §F.2
- (2020). The Alignment Problem. W. W. Norton & Company. §2.1 §F.42
- (2009). Workplace safety: A meta-analysis of the roles of person and situation factors. Journal of Applied Psychology. §53.4 §F.41
- (2018). Clarifying “AI alignment”. AI Alignment (Medium). non-peer-reviewed §1.1 §1.2 Ch. 1 §20.1 §F.14
- (2019). What failure looks like. AI Alignment Forum. non-peer-reviewed §4.1 §68.6 §F.14
- (2022a). Mechanistic anomaly detection and ELK. Alignment Research Center blog. non-peer-reviewed §47.5 §F.14
- (2022b). Where I agree and disagree with Eliezer. AI Alignment Forum. non-peer-reviewed §2.6 §2.8 §3.1 §3.8 §3.9 Ch. 3 §4.4 §5.8 §31.7 §70.3 §C.5 §F.14
- (2023). Thoughts on the impact of RLHF research. LessWrong (Alignment Forum). non-peer-reviewed §2.6 §2.10 Ch. 2 §3.3 §22.3 §65.4 §68.1 §C.6 §F.43
- (2022). ELK prize results. AI Alignment Forum. non-peer-reviewed §39.7 §47.4 §F.14
- (2017). Deep reinforcement learning from human preferences. Advances in Neural Information Processing Systems. §2.4 §2.9 §3.3 §3.9 §12.2 §13.2 §13.3 Ch. 13 §22.3 Ch. 22 §C.4 §F.2 §H.2
- (2018). Supervising strong learners by amplifying weak experts. arXiv. preprint §3.5 §3.8 §28.7 §41.2 §42.7 Ch. 42 §C.4 §F.4
- (2021). Eliciting latent knowledge: How to tell if your eyes deceive you. Alignment Research Center. non-peer-reviewed §3.5 §39.7 §39.11 Ch. 39 §47.4 Ch. 47 §C.5 §F.14 §H.1
- (2022). Formalizing the presumption of independence. arXiv. preprint §3.6 §47.1 §47.5 §47.8 Ch. 47 §F.7
- (2024). Towards a Law of Iterated Expectations for Heuristic Estimators. arXiv. preprint §47.5 §47.8 §F.7
- (2025). Backdoor defense, learnability and obfuscation. Innovations in Theoretical Computer Science Conference (ITCS 2025), LIPIcs vol. 325. doi:10.4230/lipics.itcs.2025.38. §38.1 §47.6 §47.8 §47.9 Ch. 47 §48.6 Ch. 48 §F.8 §H.1
- (2025). Are DeepSeek R1 And Other Reasoning Models More Faithful? arXiv. preprint §40.3 §40.8 §F.6 §H.2
- (2024). Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-Thought. arXiv. preprint §40.3 §F.6
- (2025). Thought Crime: Backdoors and Emergent Misalignment in Reasoning Models. arXiv. preprint §32.1 §32.5 §32.9 §F.5
- (2023). DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models. International Conference on Learning Representations. §F.2
- (2023). A Toy Model of Universality: Reverse Engineering How Networks Learn Group Operations. International Conference on Machine Learning. §45.2 §45.7 §45.8 §F.7
- (2024). Summing Up the Facts: Additive Mechanisms Behind Factual Recall in LLMs. arXiv. preprint §F.11
- (2011). A Taxonomy of External and Internal Attention. Annual Review of Psychology. §F.2
- (2020). Should Artificial Intelligence Governance be Centralised? Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. §66.7 §66.9 §F.32
- (2021). Corporate Governance of Artificial Intelligence in the Public Interest. Information. §53.6 §F.41
- (2008). Technological Due Process. Washington University Law Review. §19.6 §F.33
- (1996). Using Language. Cambridge University Press. §19.5 §F.35
- (2019). Regulatory Markets for AI Safety. arXiv. preprint §63.3 §F.49
- (1987). A Comparison of Commercial and Military Computer Security Policies. 1987 IEEE Symposium on Security and Privacy. §F.22
- (2018). Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge. arXiv. preprint §F.11
- (2019). What Does BERT Look At? An Analysis of BERT's Attention. BlackboxNLP@ACL. doi:10.18653/v1/W19-4828. §F.2
- (1980). “situational” Crime Prevention: Theory and Practice. The British Journal of Criminology. §48.7 §56.6 §59.4 §F.23
- (2008). Democracy and the Logic of Political Survival. American Political Science Review. §68.2 §68.6 §68.8 §F.45
- (1934). The Use of Confidence or Fiducial Limits Illustrated in the Case of the Binomial. Biometrika. §F.56
- (2024). Gradient Routing: Masking Gradients to Localize Computation in Neural Networks. arXiv. preprint §27.2 §F.4
- (2025). Subliminal Learning: Language models transmit behavioral traits via hidden signals in data. arXiv. preprint §1.7 §10.1 Ch. 10 §27.5 §27.7 §27.9 §32.5 §32.6 §32.9 Ch. 32 §57.6 §69.4 §69.8 §C.7 §E.3 §F.9
- (2023). Generalization Analogies: A Testbed for Generalizing AI Oversight to Hard-To-Measure Domains. arXiv. preprint §26.3 §42.4 §42.6 §F.4
- (2024). Safety Cases: How to Justify the Safety of Advanced AI Systems. arXiv. preprint §3.7 §24.7 §51.3 §52.2 §52.4 §52.5 §52.8 Ch. 52 §C.6 §F.8
- (2025). Bare Minimum Mitigations for Autonomous AI Development. arXiv. preprint §55.5 §55.6 §F.8
- (2007). The Goals and Promise of the Sarbanes–Oxley Act. Journal of Economic Perspectives. §64.6 §67.2 §F.49
- (2021). Training Verifiers to Solve Math Word Problems. arXiv. preprint §F.11
- (2020). Why Arms Control Is So Rare. American Political Science Review. §64.3 §64.10 Ch. 64 §65.6 §66.3 §66.9 Ch. 66 §D.2 §F.32 §H.3
- (2010). Robot rights? Towards a social-relational justification of moral consideration. Ethics and Information Technology. §21.6 §21.9 §F.44
- (2006). Gatekeepers: The Professions and Corporate Governance. Oxford University PressOxford. §38.6 §61.4 §67.2 §F.49
- (2025). Adversarial testing of global neuronal workspace and integrated information theories of consciousness. Nature. §3.8 §21.2 §21.9 §F.44 §H.3
- (2003). Management-Based Regulation: Prescribing Private Management to Achieve Public Goals. Law & Society Review. §1.3 §52.5 §52.7 §52.8 §61.2 §62.5 §62.9 Ch. 62 §D.3 §F.49
- (2010). Meta‐Regulation and Self‐Regulation. The Oxford Handbook of Regulation. §62.5 §F.49
- (1987). Computer viruses. Computers & Security. §58.2 §F.22
- (2020). Pessimism About Unknown Unknowns Inspires Conservatism. Conference on Learning Theory (COLT 2020), PMLR 125:1344-1373. §28.4 §F.4
- (2014). Uniform Sampling for Matrix Approximation. Information Technology Convergence and Services. doi:10.1145/2688073.2688113. §F.11
- (2020). Asymptotically Unambitious Artificial General Intelligence. Proceedings of the AAAI Conference on Artificial Intelligence. §28.4 §35.3 §F.5
- (2022). Advanced artificial agents intervene in the provision of reward. AI Magazine. §4.3 §7.6 §30.5 §F.24
- (2025). Here Comes the AI Worm: Preventing the Propagation of Adversarial Self-Replicating Prompts Within GenAI Ecosystems. Proceedings of the 2025 ACM SIGSAC Conference on Computer and Communications Security. §49.7 §57.6 §57.7 §57.9 §F.8 §H.2
- (1983). A Longitudinal Study of Moral Judgment. Monographs of the Society for Research in Child Development. §25.4 §F.57
- (1981). Prototype semantics: The English Word Lie. Language. §F.35
- (2001). An Introduction to Statistical Modeling of Extreme Values. Springer London. §6.6 §F.2
- (2019). Booting the Booters. Proceedings of the Internet Measurement Conference. §48.7 §48.9 §48.10 §56.6 §59.4 §63.7 §F.23
- (2024). Folk psychological attributions of consciousness to large language models. Neuroscience of Consciousness. §21.1 §60.3 §F.44
- (2003). Columbia Accident Investigation Board Report, Volume I. non-peer-reviewed §53.3 §53.4 §F.51
- (2025). Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities. arXiv. preprint §F.9
- (2025). The Age of AI in the Life Sciences. National Academies Press. §59.5 §F.18
- (2016). Gene Drives on the Horizon. National Academies Press. §F.18
- (2014). General comment No. 1 (2014). Article 12: Equal recognition before the law. United Nations, CRPD/C/GC/1. non-peer-reviewed §16.6 §16.11 Ch. 16 §21.6 §21.9 §60.6 §F.36
- (1996). Comprehensive Nuclear-Test-Ban Treaty (CTBT). non-peer-reviewed §66.3 §F.32
- (2025). Does It Make Sense to Speak of Introspection in Large Language Models? arXiv. preprint §21.5 §46.7 §F.7
- (1970). Every good regulator of a system must be a model of that system †. International Journal of Systems Science. §28.6 §D.9 §F.21
- (2023). Foundations of Cooperative AI. Proceedings of the AAAI Conference on Artificial Intelligence. §57.1 §57.2 §57.9 §F.9
- (2006). Computing the optimal strategy to commit to. Proceedings of the 7th ACM conference on Electronic commerce. §50.2 §F.8
- (2023). Towards Automated Circuit Discovery for Mechanistic Interpretability. Advances in Neural Information Processing Systems. §43.4 §43.8 §45.3 §45.6 §45.8 §F.7 §H.2
- (2017). How They Did It: An Analysis of Emission Defeat Devices in Modern Automobiles. 2017 IEEE Symposium on Security and Privacy (SP). §37.7 §F.43
- (1991). Experts In Uncertainty. Oxford University PressNew York, NY. §4.5 §52.4 §F.51
- (2001). Participation: The New Tyranny? Zed Books. §17.7 §F.45
- (2025). Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research. Advances in Neural Information Processing Systems 38. §27.7 §27.9 §F.4
- (2026a). A dataset of rated conceptual arguments. arXiv. preprint §F.11
- (2026b). Introducing the Conceptual Reasoning Index. Anthropic Alignment Science Blog. non-peer-reviewed §E.3 §F.58
- (2023). Power and Public Participation in AI. Equity and Access in Algorithms Mechanisms and Optimization. §17.7 §F.45
- (2019). On the Relationship between Self-Attention and Convolutional Layers. International Conference on Learning Representations. §F.2
- (2021). Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment. arXiv. preprint §5.7 §55.3 §55.9 §F.37 §H.3
- (2025). From Flat to Hierarchical: Extracting Sparse Representations with Matching Pursuit. Neural Information Processing Systems. §F.7
- (2022). Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem. 2022 ACM Conference on Fairness Accountability and Transparency. §38.6 §67.2 §F.13
- (2024). Meta-Models: An Architecture for Decoding LLM Behaviors Through Interpreted Embeddings and Natural Language. arXiv. preprint §F.11
- (2024). Reward Model Ensembles Help Mitigate Overoptimization. International Conference on Learning Representations. §15.6 §22.5 §22.10 §F.2 §H.2
- (2024). Durably reducing conspiracy beliefs through dialogues with AI. Science. §60.3 §60.10 §69.3 §F.31 §H.3
- (2021). The case for aligning narrowly superhuman models. AI Alignment Forum. non-peer-reviewed §41.1 §F.6
- (2022). Without specific countermeasures, the easiest path to transformative AI likely leads to AI takeover. AI Alignment Forum. non-peer-reviewed §3.3 §4.3 §4.7 §7.6 §24.4 §24.9 §26.1 §33.1 Ch. 33 §34.1 §70.3 Ch. 70 §C.5 §F.14
- (1923). Frye v. United States, 293 F. 1013. non-peer-reviewed §39.4 §F.33
- (2004). An Empirical Investigation of Gaming Responses to Explicit Performance Incentives. Journal of Labor Economics. §14.2 §F.25
- (1965). Geometrical and Statistical Properties of Systems of Linear Inequalities with Applications in Pattern Recognition. IEEE Transactions on Electronic Computers. §F.56
- (2006). Elements of Information Theory. Wiley. §F.56
- (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences. §F.11
- (2021). Atlas of AI. Yale University Press. §68.5 §F.12
- (1982). Strategic Information Transmission. Econometrica. §14.1 §39.2 §39.11 §F.25
- (1950). The Criminal Violation of Financial Trust. American Sociological Review. §53.5 §56.6 §D.19 §F.23
- (2022). Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning. International Conference on Learning Representations. §F.7
- (2020). AI Research Considerations for Human Existential Safety (ARCHES). arXiv. preprint §1.4 §3.8 §3.9 §14.4 §57.1 §57.4 §57.9 §61.3 §69.5 §70.3 §71.1 §F.42
- (1955). Construct validity in psychological tests. Psychological Bulletin. §5.2 §18.4 §18.7 Ch. 18 §C.1 §D.12 §F.48
- (2024). Induction Heads as an Essential Mechanism for Pattern Matching in In-context Learning. arXiv. preprint §F.2
- (2022). Sentience in decapod crustaceans: A general framework and review of the evidence. Animal Sentience. §21.4 §D.14 §F.16
- (1996). Comprehensive Nuclear-Test-Ban Treaty. non-peer-reviewed §66.3 §F.30
- (2024). OR-Bench: An Over-Refusal Benchmark for Large Language Models. International Conference on Machine Learning. §20.1 §20.6 §20.8 §F.3 §H.2
- (2025). The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models. arXiv. preprint §24.4 §24.9 §F.4
- (2025). Preference Learning with Lie Detectors can Induce Honesty or Evasion. Neural Information Processing Systems. §39.8 §39.11 §46.9 §47.7 §F.7 §H.2
- (2023). Sparse Autoencoders Find Highly Interpretable Features in Language Models. International Conference on Learning Representations. §3.6 §3.9 §5.7 §44.5 §44.8 §F.7 §H.2
- (2026). Constitutional Classifiers++: Efficient Production-Grade Defenses against Universal Jailbreaks. arXiv. preprint §23.2 §48.5 §48.8 §48.9 §59.3 §59.8 §E.1 §F.8
- (2024). A Right to Warn about Advanced Artificial Intelligence. righttowarn.ai. non-peer-reviewed §2.5 §2.6 §2.9 §2.11 §53.4 Ch. 61 §61.2 §61.3 §62.6 §67.4 §C.6 §F.13
- (2019). Is It Good to Cooperate? Testing the Theory of Morality-as-Cooperation in 60 Societies. Current Anthropology. §18.2 §18.10 §F.38
- (1989). Approximation by superpositions of a sigmoidal function. Mathematics of Control, Signals, and Systems. §8.2 §F.2
- (2023). 生成式人工智能服务管理暂行办法 (Interim Measures for the Management of Generative Artificial Intelligence Services). Cyberspace Administration of China, Order No. 15. non-peer-reviewed §2.7 §2.11 §17.5 §61.3 §63.2 §65.1 §66.1 §C.6 §F.45
- (2025). Eliciting Secret Knowledge from Language Models. arXiv. preprint §38.2 §38.4 §38.7 §38.8 §38.10 §47.7 §F.7
- (2015). Code Reviews Do Not Find Bugs. How the Current Code Review Best Practice Slows Us Down. 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering. §51.2 §F.50
D
- (2022). Underspecification Presents Challenges for Credibility in Modern Machine Learning. Journal of Machine Learning Research, 23(226):1−61. §5.1 §9.1 Ch. 9 §31.9 Ch. 31 Ch. 42 §C.5 §F.5
- (2020). A distributional code for value in dopamine-based reinforcement learning. Nature. §29.3 §29.9 §F.39
- (2023). AI Governance. The Oxford Handbook of AI Governance. §63.1 §65.1 §F.45
- (2020). Open Problems in Cooperative AI. arXiv. preprint §3.8 §57.1 §57.2 Ch. 57 §71.1 Ch. 71 §F.9
- (1957). The concept of power. Behavioral Science. §35.2 §68.1 §F.45
- (2021). Knowledge Neurons in Pretrained Transformers. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2022.acl-long.581. §F.7
- (2024). Safe RLHF: Safe Reinforcement Learning from Human Feedback. International Conference on Learning Representations. §20.6 §22.3 §28.2 §F.4
- (2024). Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems. arXiv. preprint §3.7 §3.8 §28.6 §28.8 §28.9 Ch. 28 §47.3 §52.4 §F.24
- (2004). Adversarial classification. Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining. §48.1 §F.22
- (2020). Welcoming Robots into the Moral Circle: A Defence of Ethical Behaviourism. Science and Engineering Ethics. §21.6 §F.44
- (2002). The emperor has no clothes: Limits to risk modelling. Journal of Banking & Finance. §57.4 §64.6 §67.3 §F.27
- (2018). Technology Roulette: Managing Loss of Control as Many Militaries Pursue Technological Superiority. Center for a New American Security. non-peer-reviewed §65.3 §F.25
- (1973). Free Competition and the Optimal Amount of Fraud. The Journal of Law and Economics. §14.1 §61.1 §F.46
- (2025). AI Cyber Challenge marks pivotal inflection point for cyber defense. DARPA. non-peer-reviewed §58.5 §58.10 §F.22 §H.2
- (2020). FDA Approval and Regulation of Pharmaceuticals, 1983-2018. JAMA. §52.6 §63.6 §64.5 §F.36
- (2025). CytoSAE: Interpretable Cell Embeddings for Hematology. International Conference on Medical Image Computing and Computer-Assisted Intervention. §F.7
- (1980). Uncertainty, Industrial Structure, and the Speed of R&D. The Bell Journal of Economics. §65.2 §F.25
- (2022). Dealing with Disagreements: Looking Beyond the Majority Vote in Subjective Annotations. Transactions of the Association for Computational Linguistics. §18.4 §18.10 §22.7 §F.38 §H.3
- (2023a). What a compute-centric framework says about AI takeoff speeds. LessWrong (summary of an Open Philanthropy report). non-peer-reviewed §4.3 §65.5 §68.5 §F.10
- (2023b). What a compute-centric framework says about takeoff speeds. Open Philanthropy. non-peer-reviewed §F.8
- (2023). AI capabilities can be significantly improved without expensive retraining. arXiv. preprint §5.1 §36.2 Ch. 36 §58.3 §F.9
- (2024). Self-Recognition in Language Models. Conference on Empirical Methods in Natural Language Processing. §F.2
- (2025). AI-Enabled Coups: How a Small Group Could Use AI to Seize Power. Forethought. non-peer-reviewed §1.4 §4.1 §35.6 §38.5 Ch. 38 §51.1 §51.4 Ch. 51 §53.5 §61.6 Ch. 68 §68.1 §68.2 §68.3 §68.4 §68.6 §68.8 Ch. 68 §69.3 §F.45
- (2023). Discovering Variable Binding Circuitry with Desiderata. arXiv. preprint §F.7
- (1998). Through Our Eyes Only? Oxford University Press. §F.16
- (2008). The Science of Animal Suffering. Ethology. §21.4 §F.16
- (1981). Auditor size and audit quality. Journal of Accounting and Economics. §38.6 §67.2 §F.49
- (2024a). AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. Advances in Neural Information Processing Systems. §49.3 §49.6 §49.10 §F.8 §H.2
- (2024b). Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition. Advances in Neural Information Processing Systems. §48.1 §49.5 §F.8
- (2026). Defeating Prompt Injections by Design. 2026 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML). §28.5 §28.9 §49.6 §49.10 Ch. 49 §70.3 §F.8
- (1999). A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychological Bulletin. §25.1 §25.2 §25.3 §25.9 §25.10 §33.2 §69.3 §C.2 §D.11 §F.57 §H.3
- (2001). Extrinsic Rewards and Intrinsic Motivation in Education: Reconsidered Once Again. Review of Educational Research. §F.47
- (2024). Do Unlearning Methods Remove Information from Language Model Weights? arXiv. preprint §27.7 §27.9 Ch. 27 §F.4 §H.2
- (2024). Frontier Safety Framework. Google DeepMind. non-peer-reviewed §F.13 §I.2
- (2025a). Google DeepMind strengthens the Frontier Safety Framework. Google DeepMind blog. non-peer-reviewed §62.3 §C.7 §F.10 §I.2
- (2025b). Updating the Frontier Safety Framework. Google DeepMind. non-peer-reviewed §F.13 §I.2
- (2026). Frontier Safety Framework, Version 3.1. Google DeepMind. non-peer-reviewed §2.6 §34.8 §52.1 §52.6 §59.2 §62.1 §62.2 §62.3 §62.4 §62.5 §62.6 §62.9 §67.5 §C.8 §F.13 §I.2
- (2024). DeepSeek-V3 Technical Report. arXiv. preprint §F.11
- (2025). DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning. Nature. doi:10.1038/s41586-025-09422-z. §11.4 §12.4 §12.7 Ch. 24 §24.1 §24.9 §30.2 §40.1 §40.2 §F.5
- (2017). What is consciousness, and could machines have it? Science. §21.2 §F.3
- (2010). Drift into failure: from hunting broken components to understanding complex systems. Ashgate. §53.3 §F.41
- (2024). Mapping Technical Safety Research at AI Companies: A literature review and incentives analysis. arXiv. preprint §3.1 §3.9 §5.6 §53.7 §65.4 §65.8 §F.8
- (2024). Language Modeling Is Compression. International Conference on Learning Representations. §6.2 §F.2
- (2023). The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice. Equity and Access in Algorithms, Mechanisms, and Optimization. §17.7 §F.45
- (1978). Hints on Test Data Selection: Help for the Practicing Programmer. Computer. §24.2 §D.10 §F.50
- (2019). Embedded Agency. arXiv. preprint §3.2 §7.6 Ch. 7 §F.24
- (2014). The Global War for Internet Governance. Yale University Press. §64.7 §F.30
- (2023). Multilingual Jailbreak Challenges in Large Language Models. arXiv. preprint §26.6 §26.9 §31.5 §31.9 §36.4 §48.2 §48.9 §F.8 §H.2
- (2024). From Explicit CoT to Implicit CoT: Learning to Internalize CoT Step by Step. arXiv. preprint §40.2 §F.6
- (2024). Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models. arXiv. preprint §3.3 §5.7 §22.6 §29.4 §30.5 §30.7 §30.8 Ch. 30 §C.6 §E.1 §E.3 §F.5
- (1987). The Intentional Stance. The MIT Press. §1.5 §C.2 §D.18 §F.42
- (1991). Real Patterns. The Journal of Philosophy. §F.43
- (1971). Intentional Systems. Journal of Philosophy. §1.5 §F.43
- (1987). An Intrusion-Detection Model. IEEE Transactions on Software Engineering. §51.1 §58.7 §F.22
- (1966). Programming semantics for multiprogrammed computations. Communications of the ACM. §F.22
- (2023). Introducing the AI Safety Institute. UK Government (GOV.UK). non-peer-reviewed §63.2 §63.3 §66.6 §67.6 §F.13
- (2024). Frontier AI Safety Commitments, AI Seoul Summit 2024. UK Government (GOV.UK). non-peer-reviewed §2.7 §52.1 §62.1 §62.3 §62.4 §62.5 Ch. 62 §65.4 §66.1 §C.6 §F.13 §I.5
- (2026). Command and Control. Army Doctrine Publication ADP 6-0, Headquarters, Department of the Army. non-peer-reviewed §19.7 §D.2 §F.19
- (2003). Cues to deception. Psychological Bulletin. §39.3 §F.34
- (2026). Turn-Averaged SAEs for Feature Discovery and Long-Context Attribution. arXiv. preprint §F.7
- (2022). LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale. arXiv. preprint §F.2
- (2018). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. North American Chapter of the Association for Computational Linguistics. doi:10.18653/v1/N19-1423. §F.2
- (1999). Advocates. Journal of Political Economy. §41.7 §F.53
- (2019). The Extended Corporate Mind: When Corporations Use AI to Break the Law. SSRN Electronic Journal. working paper §63.4 §F.33
- (2022). CrowdWorkSheets: Accounting for Individual and Collective Identities Underlying Crowdsourced Dataset Annotation. 2022 ACM Conference on Fairness Accountability and Transparency. §18.5 §67.5 §F.12
- (2023). Jump to Conclusions: Short-Cutting Transformers With Linear Transformations. International Conference on Language Resources and Evaluation. §F.2
- (2024). Technology and the Rise of Great Powers. Princeton University Press. §65.5 §F.32
- (2023). Enhancing Chat Language Models by Scaling High-quality Instructional Conversations. Conference on Empirical Methods in Natural Language Processing. §F.4
- (2024). Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization. Advances in Neural Information Processing Systems. §42.4 §F.6
- (1996). The Making of Economic Policy. The MIT Press. §F.25
- (1997). Power of Incentives in Private versus Public Organizations. American Economic Review (Papers and Proceedings), vol. 87(2), pp. 378-382. §14.4 §F.25
- (2002). Incentives and Organizations in the Public Sector: An Interpretative Review. The Journal of Human Resources. §14.4 §F.25
- (1997). Common Agency and Coordination: General Theory and Application to Government Policy Making. Journal of Political Economy. §1.4 §14.4 Ch. 14 §49.8 §61.3 §61.8 §61.9 Ch. 61 §69.5 §D.1 §F.25
- (2022). System Safety and Artificial Intelligence. 2022 ACM Conference on Fairness Accountability and Transparency. §52.2 §F.51
- (2021). Hard choices in artificial intelligence. Artificial Intelligence. §17.3 §F.55
- (2021). Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus. arXiv. preprint §27.3 §27.9 §27.10 §69.3 §F.4 §H.2
- (2024). Questioning the Survey Responses of Large Language Models. Advances in Neural Information Processing Systems. §18.7 §18.8 §18.10 §26.5 §26.9 §70.3 §F.38 §H.2
- (2021). Attention is Not All You Need: Pure Attention Loses Rank Doubly Exponentially with Depth. International Conference on Machine Learning. §F.2
- (2006). Compressed sensing. IEEE Transactions on Information Theory. §44.2 §F.7
- (2017). Towards A Rigorous Science of Interpretable Machine Learning. arXiv. preprint §43.1 §F.7
- (2010). Trust and technology: the social foundations of aviation regulation. The British Journal of Sociology. §52.1 §52.5 §52.7 §64.4 Ch. 64 §F.30
- (2011). “737-Cabriolet”: The Limits of Knowledge and the Sociology of Inevitable Failure. American Journal of Sociology. §52.1 §F.30
- (1978). Guaranteed margins for LQG regulators. IEEE Transactions on Automatic Control. §D.9 §F.21
- (2010). Quality Disclosure and Certification: Theory and Practice. Journal of Economic Literature. §54.6 §67.2 §67.3 §67.4 §67.8 Ch. 67 §F.25
- (2003). Is More Information Better? The Effects of “Report Cards” on Health Care Providers. Journal of Political Economy. §14.2 §15.2 §53.1 §53.9 §F.25 §H.3
- (1962). A Sampling Inspection Problem in Arms Control Agreements: A Game-Theoretic Analysis. RAND Corporation (RM-2972-ARPA). non-peer-reviewed §14.6 §66.4 §66.9 §C.1 §D.6 §F.40
- (2019). Reframing Superintelligence: Comprehensive AI Services as General Intelligence. Future of Humanity Institute, University of Oxford, Technical Report 2019-1. non-peer-reviewed §3.7 §3.8 §28.5 §F.43
- (2006). Contextual information renders experts vulnerable to making erroneous identifications. Forensic Science International. §38.7 §F.34
- (2025). Output Supervision Can Obfuscate the Chain of Thought. arXiv. preprint §40.5 §40.8 §F.6
- (2023). Improving Factuality and Reasoning in Language Models through Multiagent Debate. International Conference on Machine Learning. §57.5 §F.9
- (2022). Successive Prompting for Decomposing Complex Questions. Conference on Empirical Methods in Natural Language Processing. §F.11
- (2013). Truth-telling by Third-party Auditors and the Response of Polluting Firms: Experimental Evidence from India*. The Quarterly Journal of Economics. §37.7 §38.6 §38.10 §38.11 Ch. 38 §61.2 §67.8 Ch. 67 §69.3 §71.2 §71.6 §D.5 §F.49 §H.5
- (2006). On Doctors, Mechanics, and Computer Specialists: The Economics of Credence Goods. Journal of Economic Literature. §14.1 §61.1 §61.4 §61.8 Ch. 61 §D.1 §F.46
- (2024). Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformers. Annual Meeting of the Association for Computational Linguistics. §46.6 §F.7
- (1998). The Borda count and agenda manipulation. Social Choice and Welfare. §17.1 §F.52
- (2024). Transcoders Find Interpretable LLM Feature Circuits. Advances in Neural Information Processing Systems. §45.4 §45.8 §F.7
- (2025). Understanding Artificial Agency. The Philosophical Quarterly. §F.42
- (2004). The Three Es of Cancer Immunoediting. Annual Review of Immunology. §29.7 §51.4 §D.16 §F.17
- (2023). Cyborgism. LessWrong (Alignment Forum). non-peer-reviewed §28.7 §55.1 §F.43
- (2023). Towards Measuring the Representation of Subjective Global Opinions in Language Models. arXiv. preprint §17.4 §17.8 §26.6 §F.38
- (1967). The Model of Rules. The University of Chicago Law Review. §F.33
- (1988). The Theory and Practice of Autonomy. Cambridge University Press. §F.42
- (1972). Paternalism. Monist. §16.9 §F.42
- (1985). Disclosure of Nonproprietary Information. Journal of Accounting Research. §54.6 §D.1 §F.25
- (2026). How Vulnerable Are AI Agents to Indirect Prompt Injections? Insights from a Large-Scale Public Competition. arXiv. preprint §49.4 §F.8
E
- (2024). A Personalized Patient Preference Predictor for Substituted Judgments in Healthcare: Technically Feasible and Ethically Desirable. The American Journal of Bioethics. §16.6 §16.11 §18.6 §D.17 §F.36
- (1985). A Theoretical Basis for the Analysis of Multiversion Software Subject to Coincident Errors. IEEE Transactions on Software Engineering. §6.7 §50.4 §50.6 §52.3 §52.7 §52.8 §57.4 §69.3 §F.8 §H.1
- (2020). Reinforcement Learning Under Moral Uncertainty. arXiv. preprint §7.2 §16.3 §16.11 §F.42
- (1999). Psychological Safety and Learning Behavior in Work Teams. Administrative Science Quarterly. §53.4 §53.9 §F.41
- (1979). Contested Terrain: The Transformation of the Workplace in the Twentieth Century. Basic Books. §51.3 §F.54
- (1996). The Closed World: Computers and the Politics of Discourse in Cold War America. §2.1 §F.30
- (2011). Tweedie’s Formula and Selection Bias. Journal of the American Statistical Association. §7.7 §15.3 §F.40
- (2011). Dictators and Their Viziers: Endogenizing the Loyalty-competence Trade-off. Journal of the European Economic Association. §14.5 §51.3 §51.6 Ch. 51 §65.3 §68.4 §F.25
- (1989). Agency Theory: An Assessment and Review. The Academy of Management Review. §53.1 §F.41
- (1953). Atoms for Peace speech. non-peer-reviewed §64.3 §F.30
- (2024). On Goodhart's law, with an application to value alignment. arXiv. preprint §15.1 §15.5 §C.2 §F.25
- (2024). A Mechanism-Based Approach to Mitigating Harms from Persuasive Generative AI. arXiv. preprint §60.3 §F.42
- (2021). Amnesic Probing: Behavioral Explanation with Amnesic Counterfactuals. Transactions of the Association for Computational Linguistics. doi:10.1162/tacl_a_00359. §43.2 §43.8 §F.7 §H.2
- (2021a). A Mathematical Framework for Transformer Circuits. Transformer Circuits Thread. non-peer-reviewed §3.6 §11.2 Ch. 11 §43.1 §43.7 §45.1 §45.2 §45.9 Ch. 45 §E.4 §F.2
- (2021b). Garcon. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2022a). Softmax Linear Units. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2022b). Toy Models of Superposition. Transformer Circuits Thread. non-peer-reviewed §1.7 §3.6 §5.7 §44.1 §44.2 §44.3 §44.4 §44.5 §44.6 §44.8 Ch. 44 §69.4 §C.5 §E.4 §F.7 §H.2
- (2023). Privileged Bases in the Transformer Residual Stream. Transformer Circuits Thread. non-peer-reviewed §44.1 §E.4 §F.7
- (2019). Moral Crumple Zones: Cautionary Tales in Human-Robot Interaction. Engaging Science, Technology, and Society. §60.4 §63.4 §F.33
- (2009). The Endurance of National Constitutions. Cambridge University Press. §19.2 §F.33
- (1961). Risk, Ambiguity, and the Savage Axioms. The Quarterly Journal of Economics. §7.2 §F.24
- (2023). Artificial Intelligence (AI) in Islamic Ethics: Towards Pluralist Ethical Benchmarking for AI. Philosophy & Technology. §16.7 §F.20
- (2018). Adversarial Reprogramming of Neural Networks. International Conference on Learning Representations. §F.8
- (1979). Ulysses and the Sirens: studies in rationality and irrationality. Cambridge University Press. §61.5 §F.33
- (2000). What Makes Clinical Research Ethical? JAMA. §F.36
- (2021). Algorithmovigilance—Advancing Methods to Analyze and Monitor Artificial Intelligence–Driven Health Care for Effectiveness and Equity. JAMA Network Open. §F.36
- (2000). Item Response Theory for Psychologists. Mahwah, N.J. : L. Erlbaum Associates. §36.4 §D.12 §F.48
- (2024). Uncertainty, Information, and Risk in International Technology Races. Journal of Conflict Resolution. §65.2 §65.8 §F.29
- (2025). When Chain of Thought is Necessary, Language Models Struggle to Evade Monitors. arXiv. preprint §40.2 §40.4 §40.5 §40.8 Ch. 40 §70.3 §F.6 §H.2
- (1962). Augmenting Human Intellect: a Conceptual Framework. Defense Technical Information Center. non-peer-reviewed §3.5 §28.7 §F.43
- (2024). Not All Language Model Features Are One-Dimensionally Linear. International Conference on Learning Representations. §44.6 §44.8 §F.7
- (2025). Scaling Laws For Scalable Oversight. Advances in Neural Information Processing Systems 38. doi:10.52202/085713-3254. §3.5 §4.7 §41.6 §41.10 §42.7 §70.3 §71.5 §F.6
- (2019). Adversarial Robustness as a Prior for Learned Representations. arXiv. preprint §F.7
- (1999). Delegating Powers. Cambridge University Press. §19.6 §61.1 §D.2 §F.45
- (2023). Explosive growth from AI automation: A review of the arguments. arXiv. preprint §68.5 §68.8 §F.25
- (2025). Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. §36.8 §F.6
- (2024). Artificial Intelligence and the Political Legitimacy of Global Governance. Political Studies. §17.5 §66.1 §F.45
- (2007). Rankings and Reactivity: How Public Measures Recreate Social Worlds. American Journal of Sociology. §15.2 §F.55
- (2014). Concerning RNA-guided gene drives for the alteration of wild populations. eLife. §F.18
- (2025). Will AI R&D Automation Cause a Software Intelligence Explosion? Forethought. non-peer-reviewed §4.3 §55.7 §65.5 §F.8
- (2024). KTO: Model Alignment as Prospect Theoretic Optimization. International Conference on Machine Learning. §12.6 §13.3 §22.4 §F.2
- (2026). Meet LASER: Recursive sampling for safer conversations. OpenAI Alignment Research Blog. non-peer-reviewed §36.7 §E.5 §F.6
- (2025). The General-Purpose AI Code of Practice. European Commission. non-peer-reviewed §2.7 §62.2 §62.3 §62.4 §62.5 §62.9 §63.2 §63.3 §67.2 §67.4 §67.6 §C.7 §F.13 §I.1
- (2026). AI Omnibus enters into force. Shaping Europe's digital future. non-peer-reviewed §F.13 §I.1
- (2024a). Directive (EU) 2024/2853 (Product Liability Directive). Official Journal of the European Union. non-peer-reviewed §63.1 §63.4 §63.7 §F.33 §I.1
- (2024b). Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence. Official Journal of the European Union (OJ L 2024/1689); verified on the European Commission AI Act page. non-peer-reviewed §2.7 §17.5 §27.3 §54.6 §63.2 §63.3 §63.6 §63.7 Ch. 63 §66.1 §66.5 §67.6 §C.6 §C.7 §C.8 §F.13 §I.1
- (2001). Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiology and Drug Safety. §54.5 §F.36
- (2016). Learning the Preferences of Ignorant, Inconsistent Agents. Proceedings of the AAAI Conference on Artificial Intelligence. §18.3 §22.1 §F.4
- (2021). Truthful AI: Developing and governing AI that does not lie. arXiv. preprint §20.2 §20.8 §20.9 Ch. 20 §F.3
- (2016). Avoiding Wireheading with Value Reinforcement Learning. Lecture Notes in Computer Science. §29.4 §F.39
- (2016). Self-Modification of Policy and Utility Function in Rational Agents. Lecture Notes in Computer Science. §35.4 §F.5
- (2017). Reinforcement Learning with a Corrupted Reward Channel. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence. §7.6 §30.5 §F.24
- (2018). AGI Safety Literature Review. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. §2.3 §2.4 §3.1 §F.1
- (2019). Understanding Agent Incentives using Causal Influence Diagrams. Part I: Single Action Settings. arXiv. preprint §14.7 §F.2
- (2021a). Agent Incentives: A Causal Perspective. Proceedings of the AAAI Conference on Artificial Intelligence. §14.7 §35.3 §F.24
- (2021b). Reward tampering problems and solutions in reinforcement learning: a causal influence diagram perspective. Synthese. §3.3 §7.6 §14.7 §19.1 §29.4 §30.5 §F.5
- (2025). WASP: Benchmarking Web Agent Security Against Prompt Injection Attacks. Advances in Neural Information Processing Systems 38. §49.3 §49.4 §49.10 §F.8 §H.2
- (2023). Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence. Federal Register, 88 FR 75191 (Executive Order 14110). non-peer-reviewed §2.7 §63.2 §66.5 §C.6 §F.13 §I.1
- (2025a). Ensuring a National Policy Framework for Artificial Intelligence. Federal Register, 90 FR 58499 (Executive Order 14365). non-peer-reviewed §63.2 §63.3 §63.9 §65.1 §F.13 §I.1
- (2025b). Improving the Safety and Security of Biological Research. Federal Register, 90 FR 19611 (Executive Order 14292). non-peer-reviewed §59.5 §59.7 §F.30 §I.1
- (2025c). Initial Rescissions of Harmful Executive Orders and Actions. Federal Register. non-peer-reviewed §63.2 §F.33 §I.1
- (2025d). Removing Barriers to American Leadership in Artificial Intelligence. Federal Register, 90 FR 8741 (Executive Order 14179). non-peer-reviewed §63.2 §F.13 §I.1
- (2026). Promoting Advanced Artificial Intelligence Innovation and Security. Federal Register, 91 FR 34565 (Executive Order 14409). non-peer-reviewed §58.1 §58.8 §61.3 §63.2 §63.3 §63.6 §63.7 §66.6 §67.6 §F.13 §I.1
- (2018). Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. International Conference on Learning Representations. §28.3 §F.4
- (2025). Incident Analysis for AI Agents. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. §54.6 §F.8
- (2016). Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy. Harvard University Press. §F.33
F
- (1986). A history and theory of informed consent. New York : Oxford University Press. §F.36
- (1976). Design and code inspections to reduce errors in program development. IBM Systems Journal. §51.2 §F.50
- (2004). Enough: The Failure of the Living Will. The Hastings Center Report. §F.36
- (2001). Projection in surrogate decisions about life-sustaining medical treatments. Health Psychology. §18.6 §F.36
- (1983). Separation of Ownership and Control. The Journal of Law and Economics. §53.6 §F.41
- (2025). Evaluation Faking: Unveiling Observer Effects in Safety Evaluation of Frontier AI Systems. arXiv. preprint §37.4 §37.10 §F.6
- (2025). Unsupervised decoding of encoded reasoning using language model interpretability. arXiv. preprint §40.5 §F.6
- (2024). AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models. International Conference on Learning Representations. §F.2
- (2025). How AI and Human Behaviors Shape Psychosocial Effects of Extended Chatbot Use: A Longitudinal Randomized Controlled Study. arXiv. preprint §60.3 §60.10 §60.11 §F.31
- (2014). Functional MRI-based lie detection: scientific and societal challenges. Nature Reviews Neuroscience. §39.4 §F.34
- (2025). Jacobian Sparse Autoencoders: Sparsify Computations, Not Just Activations. International Conference on Machine Learning. §F.7
- (2022). Path-Specific Objectives for Safer Agent Incentives. Proceedings of the AAAI Conference on Artificial Intelligence. §14.7 §28.4 §35.6 §F.5
- (2023). Challenges with unsupervised LLM knowledge discovery. arXiv. preprint §39.7 §39.11 §42.5 §47.4 §F.7
- (2025). MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking. International Conference on Machine Learning. §3.7 §24.3 §24.5 §28.4 §28.9 Ch. 28 §30.8 §33.1 §F.5 §H.1
- (2019). Weaponized Interdependence: How Global Economic Networks Shape State Coercion. International Security. §66.5 §F.32
- (2025). Large AI models are cultural and social technologies. Science. §1.6 Ch. 1 §11.7 §14.8 Ch. 26 §26.1 §57.6 §57.9 Ch. 57 §68.6 §70.3 §D.16 §F.43
- (2015). Sparse Overcomplete Word Vector Representations. Annual Meeting of the Association for Computational Linguistics. doi:10.3115/v1/P15-1144. §F.7
- (2006). An introduction to ROC analysis. Pattern Recognition Letters. §6.7 §F.2
- (1995). Rationalist explanations for war. International Organization. §61.5 §65.3 Ch. 65 §F.32
- (1999). Electoral Accountability and the Control of Politicians: Selecting Good Types versus Sanctioning Poor Performance. Democracy, Accountability, and Representation. §14.5 §69.7 §F.45
- (1992). Command and Control in Emerging Nuclear Nations. International Security. §51.3 §64.3 §68.4 §F.19
- (1996). The Civil-Military Problematique: Huntington, Janowitz, and the Question of Civilian Control. Armed Forces & Society. §14.5 §19.7 §20.5 §51.3 §68.4 §D.2 §F.19
- (2003). Armed Servants. Harvard University Press. §51.3 §68.4 §C.3 §D.2 §F.19
- (2021). Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity. Journal of machine learning research. §11.2 §F.2
- (2022). A Review of Sparse Expert Models in Deep Learning. arXiv. preprint §F.11
- (2025). Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models. International Conference on Machine Learning. §F.7
- (2023). How do Language Models Bind Entities in Context? International Conference on Learning Representations. §F.2
- (2022). Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare. npj Digital Medicine. §54.5 §F.36
- (2023). Case Repositories: Towards Case-Based Reasoning for AI Alignment. arXiv. preprint §19.4 §23.7 §F.20
- (1967). The Concept of Representation. University of California Press. §1.2 §20.7 Ch. 20 §D.2 §F.45
- (1984). Slavery and Supervision in Comparative Perspective: A Model. The Journal of Economic History. §22.7 §51.3 §F.54
- (1986). Incumbent performance and electoral control. Public Choice. §14.5 §F.45
- (2024). On the Similarity of Circuits across Languages: a Case Study on the Subject-verb Agreement Task. Conference on Empirical Methods in Natural Language Processing. §F.7
- (2024). Information Flow Routes: Automatically Interpreting Language Models at Scale. Conference on Empirical Methods in Natural Language Processing. §F.2
- (2024a). A Primer on the Inner Workings of Transformer-based Language Models. arXiv. preprint §F.2
- (2024b). Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models. International Conference on Learning Representations. §F.2
- (2020a). Multi-Principal Assistance Games. arXiv. preprint §1.4 §3.2 §14.4 §17.2 §22.2 §F.25
- (2020b). Multi-Principal Assistance Games: Definition and Collegial Mechanisms. arXiv. preprint §17.1 §17.2 §17.8 §F.25
- (2024). How Do Multilingual Language Models Remember Facts? arXiv. preprint §F.2
- (2025). Parameterized Synthetic Text Generation with SimpleStories. Neural Information Processing Systems. §F.11
- (2021). The Clinician and Dataset Shift in Artificial Intelligence. New England Journal of Medicine. §54.5 §F.36
- (2016). Constructing Norms for Global Cybersecurity. American Journal of International Law. §58.8 §66.3 §F.30
- (2026). From Entropy to Epiplexity: Rethinking Information for Computationally Bounded Intelligence. arXiv. preprint §6.2 §F.2
- (2024). NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals. arXiv. preprint §38.8 §43.7 §47.7 §63.7 §67.6 §F.45
- (1952). Ethical Absolutism and the Ideal Observer. Philosophy and Phenomenological Research. §2.3 §16.2 §F.42
- (1991). Value elicitation: Is there anything in there? American Psychologist. §13.6 §18.3 §F.38
- (1978). How safe is safe enough? A psychometric study of attitudes towards technological risks and benefits. Policy Sciences. §4.2 §F.51
- (2023). Generative Social Choice. arXiv. preprint §1.7 §17.2 §17.7 §F.42
- (2024). Algorithmic Collusion by Large Language Models. arXiv. preprint §57.3 §57.7 §57.9 §F.25
- (2011). A selective role for dopamine in stimulus–reward learning. Nature. §25.5 §25.9 §29.5 §29.9 §33.2 §F.15 §H.3
- (2023). Evaluating Superhuman Models with Consistency Checks. 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML). doi:10.1109/SaTML59370.2024.00017. §F.6
- (2025). The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret. International Conference on Machine Learning. §12.8 §15.4 §22.5 §F.2
- (2026). CryptanalysisBench: Can LLMs do Cryptanalysis? arXiv. preprint §F.11
- (2014). Legislating personhood: realising the right to support in exercising legal capacity. International Journal of Law in Context. §16.6 §F.12
- (2017). Interpretable Explanations of Black Boxes by Meaningful Perturbation. IEEE International Conference on Computer Vision. doi:10.1109/ICCV.2017.371. §F.7
- (2002). Self-nonself discrimination in a computer. Proceedings of 1994 IEEE Computer Society Symposium on Research in Security and Privacy. §F.17
- (1976). The internal model principle of control theory. Automatica. §F.21
- (1995). Mutual policing and repression of competition in the evolution of cooperative groups. Nature. §29.7 §29.9 §29.10 Ch. 29 §57.2 §D.16 §F.17
- (1983). Fiduciary Law. California Law Review. §19.3 §56.8 §61.5 §D.3 §F.33
- (1971). Freedom of the Will and the Concept of a Person. The Journal of Philosophy. §F.42
- (2018). The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks. International Conference on Learning Representations. §8.3 §F.2
- (2019). Linear Mode Connectivity and the Lottery Ticket Hypothesis. International Conference on Machine Learning. §8.3 §F.2
- (2023). SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot. International Conference on Machine Learning. §F.2
- (1997). A Scientific Conception of Animal Welfare that Reflects Ethical Concerns. Animal Welfare. §21.4 Ch. 21 §D.14 §F.16
- (1987). Equipoise and the Ethics of Clinical Research. New England Journal of Medicine. §F.36
- (2001). Professionalism, the Third Logic: On the Practice of Knowledge. University of Chicago Press. §25.6 §61.4 §D.4 §F.46
- (2001). Motivation Crowding Theory. Journal of Economic Surveys. §25.3 §F.25
- (2019). Value Sensitive Design. The MIT Press. §F.55
- (1996). Bias in computer systems. ACM Transactions on Information Systems. §17.3 §F.55
- (2024). Interpretability Illusions in the Generalization of Simplified Models. International Conference on Machine Learning. §47.2 §47.8 §F.7
- (2026). Petri 2.0: New Scenarios, New Model Comparisons, and Improved Eval-Awareness Mitigations. Anthropic Alignment Science Blog. non-peer-reviewed §37.6 §37.8 §38.4 §56.3 §E.3 §F.9
- (2016). Do Arms Control Treaties Work? Assessing the Effectiveness of the Nuclear Nonproliferation Treaty. International Studies Quarterly. §64.3 §66.3 §F.32
- (1949). The Case of the Speluncean Explorers. Harvard Law Review. §F.33
- (1958). Positivism and Fidelity to Law: A Reply to Professor Hart. Harvard Law Review. §19.4 §D.3 §F.33
- (1964). The morality of law. Yale University Press. §F.33
- (2006). Varieties of Participation in Complex Governance. Public Administration Review. §17.7 §F.45
- (2007). Full Disclosure. Cambridge University Press. §67.3 §67.4 §67.8 Ch. 67 §F.49
- (1993). Science for the post-normal age. Futures. §F.37
- (2018). Born Again Neural Networks. International Conference on Machine Learning. §F.2
- (2023). Pause Giant AI Experiments: An Open Letter. Future of Life Institute. non-peer-reviewed §2.7 §3.8 §64.8 §65.6 §C.6 §F.25
- (2025). AI Safety Index: Summer 2025. Future of Life Institute. non-peer-reviewed §52.5 §61.6 §61.8 §62.7 §62.9 §65.4 §67.4 §F.25 §I.5
G
- (2026). From Simulation to Enaction: Post-trained language models recognize and react to their own generations. arXiv. preprint §F.2
- (2020). Artificial Intelligence, Values, and Alignment. Minds and Machines. §1.1 §1.2 Ch. 1 §16.1 §16.3 §16.4 §16.5 §16.7 §16.8 §16.11 Ch. 16 §C.5 §D.18 §F.42
- (2025). A matter of principle? AI alignment as the fair treatment of claims. Philosophical Studies. §16.2 §16.8 §17.5 §F.42
- (2024). The Ethics of Advanced AI Assistants. arXiv. preprint §1.4 §F.42
- (2023). "I wouldn't say offensive but...": Disability-Centered Perspectives on Large Language Models. 2023 ACM Conference on Fairness Accountability and Transparency. §20.3 §20.8 §60.7 §F.12
- (2007). Slackers and Zealots: Civil Service, Policy Discretion, and Bureaucratic Expertise. American Journal of Political Science. §19.6 §F.45
- (2012). Formal Models of Bureaucracy. Annual Review of Political Science. §61.1 §61.5 §F.45
- (2023). Bias and Fairness in Large Language Models: A Survey. Computational Linguistics. doi:10.1162/coli_a_00524. §F.2
- (2025). Instrumental divergence. Philosophical Studies. §4.4 §35.1 §F.24
- (2026). Auditing Sabotage Bench: A Benchmark for Detecting and Fixing Research Sabotage in ML Codebases. arXiv. preprint §38.2 §38.4 §38.7 §55.3 §F.8
- (2024). Interpreting the Second-Order Effects of Neurons in CLIP. International Conference on Learning Representations. §F.7
- (2026). Gaze Heads: How VLMs Look at What They Describe. arXiv. preprint §F.11
- (2012). Compressed Sensing, Sparsity, and Dimensionality in Neuronal Information Processing and Data Analysis. Annual Review of Neuroscience. §44.5 §F.7
- (2022). Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned. arXiv. preprint §3.7 §20.3 §20.8 §48.2 §F.8
- (2023). The Capacity for Moral Self-Correction in Large Language Models. arXiv. preprint §F.2
- (2020a). Making Pre-trained Language Models Better Few-shot Learners. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2021.acl-long.295. §F.2
- (2020b). The Pile: An 800GB Dataset of Diverse Text for Language Modeling. arXiv. preprint §F.2
- (2022). Scaling Laws for Reward Model Overoptimization. International Conference on Machine Learning. §3.3 §6.3 §12.5 §12.8 Ch. 12 §15.3 §15.6 Ch. 15 §22.5 §22.10 §C.5 §F.2 §H.2
- (2024). Scaling and evaluating sparse autoencoders. International Conference on Learning Representations. §44.5 §44.8 §F.7
- (2025). Weight-sparse transformers have interpretable circuits. arXiv. preprint §45.6 §45.8 §F.7
- (2015). A Comprehensive Survey on Safe Reinforcement Learning. Journal of Machine Learning Research, 16(42):1437-1480. §28.2 §F.4
- (1966). Relation of cue to consequence in avoidance learning. Psychonomic Science. §9.3 §29.5 §31.4 §D.14 §F.15
- (2026). When can we trust untrusted monitoring? A safety case sketch across collusion strategies. arXiv. preprint §50.4 §50.6 §52.5 §52.8 §57.3 §70.3 §F.8
- (2019). How does the offense-defense balance scale? Journal of Strategic Studies. §58.2 §58.10 §59.4 §65.3 §70.3 §F.32
- (2018). Counterfactual Fairness in Text Classification through Robustness. AAAI/ACM Conference on AI, Ethics, and Society. doi:10.1145/3306618.3317950. §F.8
- (2016). Logical Induction. arXiv. preprint §3.2 §7.2 §7.6 §F.24
- (2025a). Automated Researchers Can Subtly Sandbag. Anthropic Alignment Science Blog. non-peer-reviewed §34.5 §51.3 §55.5 §55.6 §55.9 Ch. 55 §C.7 §E.3 §F.8
- (2025b). Towards training-time mitigations for alignment faking in RL. Anthropic Alignment Science Blog. non-peer-reviewed §34.4 §34.7 §34.10 §E.3 §F.5
- (2024a). Automatically Identifying Local and Global Circuits with Linear Computation Graphs. arXiv. preprint §45.4 §45.8 §F.7
- (2024b). Axioms for AI Alignment from Human Feedback. Advances in Neural Information Processing Systems. §17.2 §17.8 §22.7 §F.42
- (2024). The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence. First Monday. §2.5 §2.9 §2.10 §4.4 §17.3 §61.6 §70.7 §C.6 §F.42
- (2021). Datasheets for datasets. Communications of the ACM. §27.3 §27.10 §67.5 §F.55
- (2020). RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models. Findings. doi:10.18653/v1/2020.findings-emnlp.301. §F.6
- (2021). Causal Abstractions of Neural Networks. Advances in Neural Information Processing Systems. §43.2 §43.5 §43.8 §F.7 §H.2
- (2023). Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations. CLEaR. §43.5 §F.7
- (2025). Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability. Journal of Machine Learning Research, 26(83):1−64. §3.6 §5.1 §43.3 §43.4 §43.5 §43.6 Ch. 43 §47.2 §47.8 §F.7
- (2020). Shortcut learning in deep neural networks. Nature Machine Intelligence. §8.2 §8.4 Ch. 8 §31.2 §31.9 Ch. 31 §F.5
- (2018). How Might Artificial Intelligence Affect the Risk of Nuclear War? RAND Corporation. non-peer-reviewed §59.6 §66.3 §F.32
- (2019). A Theory of Regularized Markov Decision Processes. International Conference on Machine Learning. §7.4 §F.2
- (2025). Inverse Scaling in Test-Time Compute. Trans. Mach. Learn. Res.. §31.7 §31.9 §E.3 §F.5
- (2025). Gemini Robotics: Bringing AI into the Physical World. arXiv. preprint §59.6 §F.9
- (2023). Gemini: A Family of Highly Capable Multimodal Models. arXiv. preprint §F.11
- (2024). Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context. arXiv. preprint §F.11
- (2024). Gemma 2: Improving Open Language Models at a Practical Size. arXiv. preprint §F.2
- (2025). Gemma 3 Technical Report. arXiv. preprint §F.11
- (2023). A Survey of Confidence Estimation and Calibration in Large Language Models. North American Chapter of the Association for Computational Linguistics. doi:10.18653/v1/2024.naacl-long.366. §6.4 §F.2
- (2018). Collingridge and the dilemma of control: Towards responsible and accountable innovation. Research Policy. §64.1 §F.55
- (2023). The Benefits of Bad Advice: Autocontrastive Decoding across Model Layers. Annual Meeting of the Association for Computational Linguistics. §F.11
- (2025). AI Agent Smart Contract Exploit Generation. arXiv. preprint §58.2 §F.9
- (2020). Transformer Feed-Forward Layers Are Key-Value Memories. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2021.emnlp-main.446. §F.2
- (2022a). LM-Debugger: An Interactive Tool for Inspection and Intervention in Transformer-Based Language Models. Conference on Empirical Methods in Natural Language Processing. §F.2
- (2022b). Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space. Conference on Empirical Methods in Natural Language Processing. §F.2
- (2023). Dissecting Recall of Factual Associations in Auto-Regressive Language Models. Conference on Empirical Methods in Natural Language Processing. §F.2
- (2024). Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models. International Conference on Machine Learning. §43.2 §F.7
- (2003). A century of generalization. Animal Behaviour. §F.15
- (2025). Does Thinking More always Help? Mirage of Test-Time Scaling in Reasoning Models. Neural Information Processing Systems. doi:10.52202/085713-5747. §F.11
- (2026). Natively Unlearnable Large Language Models. arXiv. preprint §27.7 §27.9 §F.4
- (1973). Manipulation of Voting Schemes: A General Result. Econometrica. §17.1 §22.8 §F.42
- (1998). Incentives in Organizations. Journal of Economic Perspectives. §14.2 §F.25
- (2023). ChatGPT outperforms crowd workers for text-annotation tasks. Proceedings of the National Academy of Sciences. §18.5 §22.7 §F.12
- (1982). In a different voice: psychological theory and women's development. Harvard University Press. §25.4 §F.57
- (2018). Adversarial Spheres. arXiv. preprint §F.8
- (2022). Improving alignment of dialogue agents via targeted human judgements. arXiv. preprint §F.9
- (2000). The Causes and Consequences of Arms Races. Annual Review of Political Science. §65.3 §F.32
- (2024). FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI. arXiv. preprint §F.6
- (2024). Identifying and Improving Disability Bias in GPT-Based Resume Screening. The 2024 ACM Conference on Fairness Accountability and Transparency. §60.7 §F.12
- (2020). Adversarial Policies: Attacking Deep Reinforcement Learning. International Conference on Learning Representations. §48.1 §F.8
- (2021). Quantifying Differences in Reward Functions. International Conference on Learning Representations. §22.5 §F.4
- (2000). A Fine is a Price. The Journal of Legal Studies. §F.25
- (2007). Strictly Proper Scoring Rules, Prediction, and Estimation. Journal of the American Statistical Association. §6.4 §F.56
- (1998). Effect on the Quality of Peer Review of Blinding Reviewers and Asking Them to Sign Their Reports. JAMA. §F.37
- (2025a). Great Models Think Alike and this Undermines AI Oversight. arXiv. preprint §41.6 §41.10 §50.4 §52.3 §57.4 §F.8
- (2025b). Learning to Interpret Weight Differences in Language Models. arXiv. preprint §38.3 §F.6
- (2024). Safety case template for frontier AI: A cyber inability argument. arXiv. preprint §52.5 §52.8 §58.3 §F.13
- (2021). Multimodal Neurons in Artificial Neural Networks. Distill. §F.7
- (1996). A Secure Environment for Untrusted Helper Applications (Confining the Wily Hacker). Sixth USENIX Security Symposium. §49.6 §F.22
- (2025). Equivalent Linear Mappings of Large Language Models. Trans. Mach. Learn. Res.. §F.2
- (2001). Experts: Which Ones Should You Trust? Philosophy and Phenomenological Research. §41.7 §D.18 §F.53
- (2023). Localizing Model Behavior with Path Patching. arXiv. preprint §45.2 §F.7
- (2025). Detecting Strategic Deception Using Linear Probes. arXiv. preprint §34.8 §39.1 §39.5 §39.6 §39.11 §46.4 §F.5 §H.2
- (2025a). AI wellbeing. Asian Journal of Philosophy. §21.1 §21.9 §F.44
- (2025b). Language agents reduce the risk of existential catastrophe. AI & SOCIETY. §4.4 §28.5 §F.43
- (2026). A Case for AI Consciousness: Language Agents and Global Workspace Theory. Journal of Consciousness Studies. doi:10.53765/20512201.33.7.061. §11.5 §21.2 §F.44
- (1985). The knowledge complexity of interactive proof-systems. Proceedings of the seventeenth annual ACM symposium on Theory of computing - STOC '85. §41.3 §F.6
- (2008). Delegating computation. Proceedings of the fortieth annual ACM symposium on Theory of computing. §41.4 §F.6
- (2022). Planting Undetectable Backdoors in Machine Learning Models : [Extended Abstract]. 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS). §27.6 §28.6 §34.3 §34.10 §38.1 §38.10 §47.1 §47.6 §47.7 §47.8 §47.9 Ch. 47 §48.6 Ch. 48 §69.4 §D.9 §F.8 §H.1
- (2025). Oblivious Defense in ML Models: Backdoor Removal without Detection. Proceedings of the 57th Annual ACM Symposium on Theory of Computing. doi:10.1145/3717823.3718245. §47.6 §47.9 §48.6 §F.8
- (1966). Speculations Concerning the First Ultraintelligent Machine. Advances in Computers. §2.2 §C.1 §F.42
- (1975). Toward a theory of test data selection. IEEE Transactions on Software Engineering. §24.2 §F.50
- (2014). Qualitatively characterizing neural network optimization problems. International Conference on Learning Representations. §8.3 §F.2
- (2015). Explaining and Harnessing Adversarial Examples. International Conference on Learning Representations (ICLR 2015). §8.2 §8.4 §48.1 §F.8
- (2016). Deep Learning. MIT Press. §F.2
- (1984). Problems of Monetary Management: The UK Experience. Monetary Theory and Practice. §15.1 §C.2 §D.1 §F.25
- (2013). Supported Decision-Making: A Rights-Based Disability Concept and its Implications for Mental Health Law. Psychiatry, Psychology and Law. §F.12
- (2016). Pragmatic Language Interpretation as Probabilistic Inference. Trends in Cognitive Sciences. §19.5 §F.35
- (2023). Will releasing the weights of future large language models grant widespread access to pandemic agents? arXiv. preprint §59.2 §63.7 §F.18
- (2024). The Missing Curve Detectors of InceptionV1: Applying Sparse Autoencoders to InceptionV1 Early Vision. arXiv. preprint §F.7
- (2026). Accelerating scientific discovery with Co-Scientist. Nature. §55.2 §57.1 §F.8
- (2023). Successor Heads: Recurring, Interpretable Attention Heads In The Wild. International Conference on Learning Representations. §45.2 §45.7 §F.7
- (2025). Act on Promotion of Research and Development, and Utilization of Artificial Intelligence-related Technology. Japanese Law Translation. non-peer-reviewed §63.2 §F.33 §I.1
- (2021). Coordination Among Neural Modules Through a Shared Global Workspace. International Conference on Learning Representations. §F.11
- (2015). The Asilomar Conference: A Case Study in Risk Mitigation. Machine Intelligence Research Institute, Technical report 2015-9. non-peer-reviewed §2.7 §2.10 §64.2 §64.8 §64.10 §F.30
- (2022). Let’s think about slowing down AI. LessWrong (Alignment Forum). non-peer-reviewed §3.8 §64.8 §64.10 §65.6 §65.8 §F.43
- (2018). Viewpoint: When Will AI Exceed Human Performance? Evidence from AI Experts. Journal of Artificial Intelligence Research. §4.5 §F.1
- (2024). Thousands of AI Authors on the Future of AI. arXiv. preprint §4.5 §4.8 §70.6 §F.28 §H.3
- (2013). Moral Foundations Theory. Advances in Experimental Social Psychology. §18.2 §18.10 Ch. 18 §20.3 §20.5 §25.4 §25.9 §F.38
- (2024). The Llama 3 Herd of Models. arXiv. preprint §F.11
- (2019). Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. Houghton Mifflin Harcourt. §18.5 Ch. 18 §22.7 §68.5 §F.12
- (2011). Human consciousness and its relationship to social neuroscience: A novel hypothesis. Cognitive Neuroscience. §F.11
- (2015). The attention schema theory: a mechanistic account of subjective awareness. Frontiers in Psychology. §F.7
- (2023). A Bargaining-Theoretic Approach to Moral Uncertainty. Journal of Moral Philosophy. §16.3 §16.11 §F.42
- (1966). Signal Detection Theory and Psychophysics. Wiley. §6.7 §F.47
- (2024). The case for ensuring that powerful AIs are controlled. LessWrong / AI Alignment Forum. non-peer-reviewed §3.7 §3.8 Ch. 50 §50.1 §51.4 §51.6 §70.3 §F.8
- (2024a). AI Control: Improving Safety Despite Intentional Subversion. International Conference on Machine Learning. §3.7 §3.9 §14.6 Ch. 50 §50.1 §50.2 §50.3 §50.4 §50.6 Ch. 50 §51.1 §51.2 §51.4 §C.6 §F.8
- (2024b). Alignment faking in large language models. arXiv. preprint §2.6 §3.4 §5.3 §5.7 §25.1 §25.7 §34.4 §34.7 §34.10 Ch. 34 §35.6 §C.6 §E.1 §E.3 §F.5
- (2024c). Stress-Testing Capability Elicitation With Password-Locked Models. Advances in Neural Information Processing Systems. §5.3 §34.5 §34.10 §36.2 §36.10 §70.3 §F.5 §H.2
- (2023). Not What You've Signed Up For: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection. Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security. §49.1 §56.5 §F.8
- (1975). Logic and Conversation. Speech Acts. §19.5 §20.2 §D.18 §F.35
- (2026). Games for AI Control: Models of Safety Evaluations of AI Deployment Protocols. Proceedings of IASEAI Conference. §14.6 §50.2 §F.8
- (1983). Thirteen theorems in search of the truth. Theory and Decision. §F.52
- (2024). Compact Proofs of Model Performance via Mechanistic Interpretability. Advances in Neural Information Processing Systems. doi:10.52202/079017-2523. §45.6 §45.8 Ch. 45 §47.3 §47.7 §F.7
- (2024). Three Sketches of ASL-4 Safety Case Components. Anthropic Alignment Science Blog. non-peer-reviewed §52.3 §52.5 §52.8 §E.3 §F.8
- (2023). Studying Large Language Model Generalization with Influence Functions. arXiv. preprint §10.1 Ch. 10 §27.1 §E.1 §E.3 §F.2
- (1981). The Informational Role of Warranties and Private Disclosure about Product Quality. The Journal of Law and Economics. §5.6 §54.6 Ch. 54 §67.1 §C.2 §D.1 §F.49
- (1980). Disclosure Laws and Takeover Bids. The Journal of Finance. §F.25
- (1986). The Costs and Benefits of Ownership: A Theory of Vertical and Lateral Integration. Journal of Political Economy. §14.3 §F.25
- (1994). Impact of parental discipline methods on the child's internalization of values: A reconceptualization of current points of view. Developmental Psychology. §25.3 §F.57
- (2017). BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain. arXiv. preprint §27.6 §34.3 §48.6 §C.4 §F.8
- (2024a). A Review of Safe Reinforcement Learning: Methods, Theories, and Applications. IEEE Transactions on Pattern Analysis and Machine Intelligence. §F.4
- (2024b). Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast. arXiv. preprint §49.7 §57.6 §57.7 §57.9 §F.36 §H.2
- (2024). Deliberative Alignment: Reasoning Enables Safer Language Models. arXiv. preprint §3.3 §20.6 §23.1 §23.3 §23.4 §23.6 §23.8 §23.9 Ch. 23 §40.6 §C.6 §F.4
- (2025). Monitoring Monitorability. arXiv. preprint §40.4 §40.8 Ch. 40 §E.5 §F.6 §I.2
- (2026a). AI Agents Enable Adaptive Computer Worms. arXiv. preprint §F.9
- (2026b). Beyond g-mean²: complementary metrics for monitorability. OpenAI Alignment Research Blog. non-peer-reviewed §40.4 §E.5 §F.6
- (2009). Assessing the Extent of Crime Displacement and Diffusion of Benefits: a Review of Situational Crime Prevention Evaluations*. Criminology. §48.7 §48.9 Ch. 48 §56.6 §59.4 Ch. 59 §63.7 §63.9 §D.19 §F.23
- (2023). LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models. Advances in Neural Information Processing Systems. §F.33
- (2024). BoNBoN Alignment for Large Language Models and the Sweetness of Best-of-n Sampling. Advances in Neural Information Processing Systems. doi:10.52202/079017-0094. §12.5 §F.2
- (2000). The nature of safety culture: a review of theory and research. Safety Science. §53.4 §F.41
- (2026). Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains. International Conference on Learning Representations. §1.7 §23.3 §24.1 §F.4
- (2026). Introducing Model Spec Evals. OpenAI Alignment Research Blog. non-peer-reviewed §19.2 §19.8 §19.9 §23.3 §23.6 §E.5 §F.4
- (2017). On Calibration of Modern Neural Networks. International Conference on Machine Learning. §6.4 §F.2
- (2025a). All Code, No Thought: Current Language Models Struggle to Reason in Ciphered Language. arXiv. preprint §F.2
- (2025b). ImageDoctor: Diagnosing Text-to-Image Generation via Grounded Image Reasoning. arXiv. preprint §F.11
- (2026). IH-Challenge: A Training Dataset to Improve Instruction Hierarchy on Frontier LLMs. arXiv. preprint §19.3 §19.9 §23.1 §49.4 §F.8
- (2024). InterpBench: Semi-Synthetic Transformers for Evaluating Mechanistic Interpretability Techniques. arXiv. preprint §43.3 §43.8 §F.7
- (2025). Enhancing Automated Interpretability with Output-Centric Feature Descriptions. Annual Meeting of the Association for Computational Linguistics. §F.7
- (2023). Language Models Represent Space and Time. International Conference on Learning Representations. §46.1 §46.9 §F.7 §H.2
- (2023). Finding Neurons in a Haystack: Case Studies with Sparse Probing. Trans. Mach. Learn. Res.. §44.1 §44.5 §F.7
- (2024). Universal Neurons in GPT2 Language Models. Trans. Mach. Learn. Res.. §44.1 §F.7
- (2025). When Models Manipulate Manifolds: The Geometry of a Counting Task. Transformer Circuits Thread. non-peer-reviewed §44.6 §44.8 §45.5 §E.4 §F.7
- (2026). Verbalizable Representations Form a Global Workspace in Language Models. Transformer Circuits Thread. non-peer-reviewed §21.2 §21.5 §21.9 §46.7 §E.4 §F.7
- (2021). DEMix Layers: Disentangling Domains for Modular Language Modeling. North American Chapter of the Association for Computational Linguistics. doi:10.18653/v1/2022.naacl-main.407. §F.2
- (2022). Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. §17.4 §27.3 §27.9 Ch. 27 §69.3 §D.20 §F.12 §H.2
- (2022). Money-Pump Arguments. Cambridge University Press. §7.2 §7.3 §7.8 §35.4 §35.8 §F.24
- (1955). The Determinacy of Factor Score Matrices with Implications for Five Other Basic Problems of Common‐factor Theory 1. British Journal of Statistical Psychology. §69.4 §F.48
- (2022). The role of the African value of Ubuntu in global AI inclusion discourse: A normative ethics perspective. Patterns. §16.7 §F.20
H
- (1992). Introduction: epistemic communities and international policy coordination. International Organization. §2.1 §66.6 §F.32
- (2023). PIGEON: Predicting Image Geolocations. Computer Vision and Pattern Recognition. doi:10.1109/CVPR52733.2024.01225. §F.11
- (2011). Do Natural Resources Fuel Authoritarianism? A Reappraisal of the Resource Curse. American Political Science Review. §68.2 §68.6 §68.8 §F.45
- (2025). The levers of political persuasion with conversational artificial intelligence. Science. §39.3 §60.3 §60.10 §68.3 §69.3 §F.31 §H.3
- (2023). Regulating ChatGPT and other Large Generative AI Models. 2023 ACM Conference on Fairness Accountability and Transparency. §63.2 §F.49
- (2009). The Nimrod Review: an independent review into the broader issues surrounding the loss of the RAF Nimrod MR2 aircraft XV230 in Afghanistan in 2006. UK House of Commons. non-peer-reviewed §52.2 §F.51
- (2026). Legal infrastructure for transformative AI governance. Proceedings of the National Academy of Sciences. §63.3 §F.33
- (2023). Regulatory Markets: The Future of AI Governance. arXiv. preprint §63.3 §F.33
- (2025). An Economy of AI Agents. arXiv. preprint §13.1 §57.3 §57.9 §F.25
- (2019). Incomplete Contracting and AI Alignment. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society. §1.7 §14.3 Ch. 14 §19.2 Ch. 19 §35.5 §35.7 Ch. 69 §71.4 §C.4 §D.1 §F.25
- (2016). Cooperative Inverse Reinforcement Learning. arXiv. preprint §2.3 §2.9 §3.2 §3.8 §22.2 §22.9 §22.10 Ch. 22 §35.5 §C.4 §F.24
- (2017a). Inverse Reward Design. Advances in Neural Information Processing Systems. §3.2 §15.6 §22.2 §F.2
- (2017b). The Off-Switch Game. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence. §3.2 §3.8 §20.4 §20.6 §20.8 Ch. 20 §22.2 §35.5 Ch. 35 §70.3 §C.4 §F.24 §H.1
- (2019). Legible Normativity for AI Alignment. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society. §F.33
- (2022). World Values Survey Trend File (1981-2022) Cross-National Data-Set. JD Systems Institute and WVSA Secretariat (World Values Survey Association). non-peer-reviewed §18.1 §F.38
- (1998). Beyond curriculum reform. Academic Medicine. §25.6 §F.46
- (2026). The Hot Mess of AI: How Does Misalignment Scale With Model Intelligence and Task Complexity? arXiv. preprint §1.5 §1.8 §4.1 §4.7 §4.8 §7.3 §31.7 §31.9 §69.5 §70.3 §E.3 §F.5
- (2020). The Ethics of AI Ethics: An Evaluation of Guidelines. Minds and Machines. §2.5 §61.4 §F.12
- (2024). Deception abilities emerged in large language models. Proceedings of the National Academy of Sciences. §34.5 §34.10 §F.5 §H.2
- (2023). Machine Psychology. arXiv. preprint §5.4 §26.5 §F.4
- (2001). The emotional dog and its rational tail: A social intuitionist approach to moral judgment. Psychological Review. §25.4 §F.57
- (2025). Position-aware Automatic Circuit Discovery. Annual Meeting of the Association for Computational Linguistics. §F.7
- (2023). Overthinking the Truth: Understanding how Language Models Process False Demonstrations. International Conference on Learning Representations. §F.2
- (2024a). Approaching Human-Level Forecasting with Language Models. Advances in Neural Information Processing Systems. §4.5 §F.28
- (2024b). Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation. International Conference on Machine Learning. §F.4
- (2011). Systemic risk in banking ecosystems. Nature. §4.6 §57.4 §F.21
- (1964). The genetical evolution of social behaviour. I. Journal of Theoretical Biology. §F.17
- (2025). Neural Interactive Proofs. International Conference on Learning Representations. §41.5 §41.9 §F.6
- (2023). Reasoning about causality in games. Artificial Intelligence. doi:10.1016/j.artint.2023.103919. §14.7 §57.2 §F.9
- (2025). Multi-Agent Risks from Advanced AI. arXiv. preprint §3.8 §4.1 §57.1 §57.2 §57.3 §57.4 §57.5 §57.7 §57.9 Ch. 57 §70.3 §F.9
- (2024). Training data influence analysis and estimation: a survey. Machine Learning. doi:10.1007/s10994-023-06495-7. §10.1 §F.2
- (2015). Learning both Weights and Connections for Efficient Neural Networks. arXiv. preprint §F.2
- (2020). To Regulate or Not: A Social Dynamics Analysis of an Idealised AI Race. Journal of Artificial Intelligence Research. §65.2 §65.5 §65.6 §65.8 §F.29
- (2022). Voluntary safety commitments provide an escape from over-regulation in AI development. Technology in Society. §62.5 §65.2 §F.29
- (2024). WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs. Advances in Neural Information Processing Systems. §F.8
- (2025). Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations. arXiv. preprint §60.6 §60.10 §68.5 §68.7 §68.8 §F.9
- (1983). If Nothing Goes Wrong, Is Everything All Right? JAMA. §6.5 Ch. 6 §F.2
- (2023). How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model. Advances in Neural Information Processing Systems. §F.2
- (2024). Have Faith in Faithfulness: Going Beyond Circuit Overlap When Finding Model Mechanisms. arXiv. preprint §45.1 §45.3 §F.7
- (2024). Mathematical Models of Computation in Superposition. arXiv. preprint §44.4 §44.8 Ch. 44 §F.7
- (1980). The Role of Nonprofit Enterprise. The Yale Law Journal. §53.6 §61.5 §F.49
- (2024). Training Large Language Models to Reason in a Continuous Latent Space. arXiv. preprint §24.3 §40.2 §F.4
- (2018). A Data-Driven Analysis of Workers' Earnings on Amazon Mechanical Turk. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. §18.5 §F.12
- (1968). The Tragedy of the Commons. Science. §65.6 §F.29
- (2004). Cognitive bias and affective state. Nature. §21.4 §F.16
- (2016). Strategic Classification. Proceedings of the 2016 ACM Conference on Innovations in Theoretical Computer Science. §15.1 §48.1 §F.25
- (1985). Epistemic Dependence. The Journal of Philosophy. §41.7 §F.53
- (1988). The Confused Deputy. ACM SIGOPS Operating Systems Review. §49.2 Ch. 49 §F.22
- (2001). Do chimpanzees know what conspecifics know? Animal Behaviour. §5.4 §34.7 §37.6 §F.15
- (2012). The self-domestication hypothesis: evolution of bonobo psychology is due to selection against aggression. Animal Behaviour. §29.6 §F.17
- (2015). The Irrelevance of Moral Uncertainty. Oxford Studies in Metaethics, Volume 10. §16.3 §16.11 §F.42
- (1987). Racing with Uncertainty. The Review of Economic Studies. §65.2 §F.25
- (1984). Decision Making and Postdecision Surprises. Administrative Science Quarterly. §7.7 §F.40
- (1955). Cardinal Welfare, Individualistic Ethics, and Interpersonal Comparisons of Utility. Journal of Political Economy. §7.2 §17.1 §F.42
- (1958). Positivism and the Separation of Law and Morals. Harvard Law Review. §19.4 §D.3 §F.33
- (1961). The concept of law. Clarendon Press. §19.4 §F.33
- (2017). Incomplete Contracts and Control. American Economic Review. §F.25
- (1990). Property Rights and the Nature of the Firm. Journal of Political Economy. §14.3 §F.25
- (1928). Studies in the nature of character, [part] 1: Studies in deceit: book 1, General methods and results; book 2, Statistical methods and results. MacMillan Co. §25.2 §26.5 §D.11 §F.57
- (2011). Why do lie-catchers fail? A lens model meta-analysis of human lie judgments. Psychological Bulletin. §39.3 §F.34
- (2026). Counterfactual Simulation Training for Chain-of-Thought Faithfulness. arXiv. preprint §40.3 §F.6
- (2023). Does Localization Inform Editing? Surprising Differences in Causality-Based Localization vs. Knowledge Editing in Language Models. Advances in Neural Information Processing Systems. §43.4 §43.8 §47.2 §F.7
- (2024). The Unreasonable Effectiveness of Easy Training Data for Hard Tasks. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). §42.4 §42.6 §42.7 §42.8 §F.6
- (2025). Don't Overthink it. Preferring Shorter Thinking Chains for Improved LLM Reasoning. arXiv. preprint §F.11
- (2022). Surprises in high-dimensional ridgeless least squares interpolation. The Annals of Statistics. doi:10.1214/21-aos2133. §9.2 §9.5 §F.2
- (2015). Are Computers Effective Lie Detectors? A Meta-Analysis of Linguistic Cues to Deception. Personality and Social Psychology Review. §39.3 §F.34
- (2023). Multinational AGI Consortium (MAGIC): A Proposal for International Coordination on AI. arXiv. preprint §66.7 §F.32
- (2011). Preference, Value, Choice, and Welfare. Cambridge University Press. §13.1 §F.25
- (2010). A New Approach to creating Clear Safety Arguments. Advances in Systems Safety. §52.2 §F.51
- (1996). The Use of Knowledge in Society. Knowledge Management and Organisational Design. §F.25
- (2006). Under-Reporting of Adverse Drug Reactions. Drug Safety. §5.1 §54.5 §D.17 §F.36
- (2015a). Deep Residual Learning for Image Recognition. Computer Vision and Pattern Recognition. doi:10.1109/cvpr.2016.90. §8.2 §F.2
- (2015b). Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification. IEEE International Conference on Computer Vision. doi:10.1109/ICCV.2015.123. §F.11
- (2024a). Dictionary Learning Improves Patch-Free Circuit Discovery in Mechanistic Interpretability: A Case Study on Othello-GPT. arXiv. preprint §F.7
- (2024b). JailbreakLens: Interpreting Jailbreak Mechanism in the Lens of Representation and Circuit. arXiv. preprint §F.7
- (2024c). Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders. arXiv. preprint §44.5 §44.8 §F.7
- (2024d). Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience. arXiv. preprint §43.6 §F.7
- (2025). Towards Understanding the Nature of Attention with Low-Rank Sparse Decomposition. arXiv. preprint §F.2
- (2001). Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature. Journal of Accounting and Economics. §67.3 §F.25
- (2003). The Fall of Enron. Journal of Economic Perspectives. §38.6 §38.10 §53.6 §64.6 §F.49
- (2025). Automated Interpretability Metrics Do Not Distinguish Trained and Random Transformers. arXiv. preprint §3.9 §44.5 §44.8 §F.7 §H.2
- (1963). Electrical Self-stimulation of the Brain in Man. American Journal of Psychiatry. §29.4 §F.39
- (2025a). How can we solve diffuse threats like research sabotage with AI control? Redwood Research blog. non-peer-reviewed §55.5 §F.14
- (2025b). How training-gamers might function (and win). AI Alignment Forum. non-peer-reviewed §24.4 §24.9 §33.1 §70.3 §F.14
- (2022). Path dependence in ML inductive biases. AI Alignment Forum. non-peer-reviewed §9.3 §70.3 §F.14
- (2024). Training Compute Thresholds: Features and Functions in AI Regulation. arXiv. preprint §63.2 §63.9 §66.5 §66.9 §F.13
- (2024). Governing Through the Cloud: The Intermediary Role of Compute Providers in AI Regulation. arXiv. preprint §66.5 §F.13
- (2024). How to use and interpret activation patching. arXiv. preprint §43.4 §F.7
- (2024). Monotonic Representation of Numeric Properties in Language Models. arXiv. preprint §F.7
- (2000). On error management: lessons from aviation. BMJ. §52.6 §53.4 §54.6 §64.4 §D.7 §F.51
- (1999). The Evolution of Crew Resource Management Training in Commercial Aviation. The International Journal of Aviation Psychology. §F.51
- (2023). In-Context Learning Creates Task Vectors. Conference on Empirical Methods in Natural Language Processing. §11.3 §F.2
- (2023). Natural Selection Favors AIs over Humans. arXiv. preprint §4.3 §28.5 §28.9 §29.1 §29.7 §29.9 §65.4 §68.6 §F.17
- (2024). Introduction to AI Safety, Ethics, and Society. CRC Press. §3.1 §17.1 §17.2 §17.5 §53.2 §53.9 §F.8
- (2016a). A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks. International Conference on Learning Representations. §8.4 §F.2
- (2016b). Gaussian Error Linear Units (GELUs). arXiv. preprint §8.2 §F.2
- (2025). The Misguided Quest for Mechanistic AI Interpretability. AI Frontiers. non-peer-reviewed §3.6 §4.7 §47.7 §70.3 §F.14
- (2018). Deep Anomaly Detection with Outlier Exposure. International Conference on Learning Representations. §F.11
- (2020a). Aligning AI With Shared Human Values. International Conference on Learning Representations. §16.1 §16.11 §F.3
- (2020b). Measuring Massive Multitask Language Understanding. International Conference on Learning Representations. §F.11
- (2021a). Measuring Coding Challenge Competence With APPS. NeurIPS Datasets and Benchmarks. §F.11
- (2021b). Measuring Mathematical Problem Solving With the MATH Dataset. NeurIPS Datasets and Benchmarks. §F.11
- (2021c). Unsolved Problems in ML Safety. arXiv. preprint §2.4 §71.1 Ch. 71 §F.1
- (2023). An Overview of Catastrophic AI Risks. arXiv. preprint §4.1 §53.2 §F.8
- (2025). Superintelligence Strategy: Expert Version. arXiv. preprint §65.2 §65.3 §65.5 §65.6 §65.8 §66.7 §70.3 §F.29
- (2020). Scaling Laws for Autoregressive Generative Modeling. arXiv. preprint §6.2 §8.5 §F.2
- (2023). Superposition, Memorization, and Double Descent. Transformer Circuits Thread. non-peer-reviewed §9.2 §44.3 §E.4 §F.2
- (2023). Goodhart's Law and Machine Learning: a Structural Perspective. International Economic Review. §15.1 §F.25
- (2001). The evolution of prestige: freely conferred deference as a mechanism for enhancing the benefits of cultural transmission. Evolution and Human Behavior. §F.17
- (2001). In Search of Homo Economicus: Behavioral Experiments in 15 Small-Scale Societies. American Economic Review. §17.4 §F.55
- (2010). The weirdest people in the world? Behavioral and Brain Sciences. §17.4 §25.4 §D.20 §F.55
- (2012). Airborne Transmission of Influenza A/H5N1 Virus Between Ferrets. Science. §59.5 §F.30
- (2017). SoK: Science, Security and the Elusive Goal of Security as a Scientific Pursuit. 2017 IEEE Symposium on Security and Privacy (SP). §48.1 §F.22
- (2016). Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available: Table 1. American Journal of Epidemiology. §5.8 §60.8 §F.36
- (2022). Scaling Laws and Interpretability of Learning from Repeated Data. arXiv. preprint §F.7
- (2023). Linearity of Relation Decoding in Transformer Language Models. International Conference on Learning Representations. §46.1 §F.7
- (2017). The Measure of All Minds. Cambridge University Press. §36.4 §F.48
- (2021). Buddhism and Intelligent Technology. Bloomsbury Academic. §16.7 §60.3 §F.20
- (1950). Idealist Internationalism and the Security Dilemma. World Politics. §65.3 §F.32
- (1963). Models and Analogies in Science. Sheed & Ward. §64.1 §69.1 §F.37
- (2017). Deep Learning Scaling is Predictable, Empirically. arXiv. preprint §8.5 §F.2
- (2019). Designing and Interpreting Probes with Control Tasks. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/D19-1275. §43.2 §43.9 §F.7
- (1998). Theory of mind in nonhuman primates. Behavioral and Brain Sciences. §1.5 §5.4 Ch. 5 §31.4 §34.7 §37.6 Ch. 37 §D.14 §F.15
- (1965). The Environment and Disease: Association or Causation? Proceedings of the Royal Society of Medicine. §5.7 §5.8 Ch. 5 §60.8 §D.17 §F.36
- (2024a). A bird's eye view of ARC's research. Alignment Research Center blog. non-peer-reviewed §3.6 §47.5 §47.7 §47.8 §F.14
- (2024b). Formal verification, heuristic explanations and surprise accounting. Alignment Research Center blog. non-peer-reviewed §47.5 §F.14
- (2020). Understanding RL vision. Distill. §F.11
- (2025). Safety Cases: A Scalable Approach to Frontier AI Safety. arXiv. preprint §24.7 §52.1 §52.2 §52.5 §F.8
- (2023). Against “Democratizing AI”. AI & SOCIETY. §17.7 §17.8 §61.6 §70.3 §F.45
- (2025). Projecting Assumptions: The Duality Between Sparse Autoencoders and Concept Geometry. Neural Information Processing Systems. §44.6 §44.8 §F.7
- (2024). Defending Against Indirect Prompt Injection Attacks With Spotlighting. arXiv. preprint §49.1 §49.5 §F.8
- (1987). How Learning Can Guide Evolution. Complex Systems, Volume 1, Issue 3. §F.17
- (2015). Distilling the Knowledge in a Neural Network. arXiv. preprint §11.4 §F.2
- (1970). Exit, Voice, and Loyalty: Responses to Decline in Firms, Organizations, and States. Harvard University Press. §61.3 §F.25
- (2026). CoVal: Learning values-aware rubrics from the crowd. OpenAI Alignment Research Blog. non-peer-reviewed §22.5 §E.5 §F.4
- (2023). International Institutions for Advanced AI. arXiv. preprint §66.6 §66.7 Ch. 66 §F.32
- (2024). Algorithmic progress in language models. Advances in Neural Information Processing Systems. §8.5 §F.2
- (2000). Empathy and Moral Development. Cambridge University Press. §25.3 Ch. 25 §F.57
- (2022). Training Compute-Optimal Large Language Models. arXiv. preprint §8.5 §43.4 §F.2
- (2026). Measuring Reward-Seeking via Contrastive Belief Updates. arXiv. preprint §4.7 §30.3 §33.1 §33.2 §33.4 §E.5 §F.5
- (2018). Safety–I and Safety–II. CRC Press. §F.51
- (1979). Moral Hazard and Observability. The Bell Journal of Economics. §14.1 §C.2 §F.25
- (2017). Pay For Performance and Beyond. American Economic Review. §14.2 §F.25
- (1987). Aggregation and Linearity in the Provision of Intertemporal Incentives. Econometrica. §F.25
- (1991). Multitask Principal–Agent Analyses: Incentive Contracts, Asset Ownership, and Job Design. The Journal of Law, Economics, and Organization. §1.3 §14.2 Ch. 14 Ch. 69 §C.2 §D.1 §F.25
- (2019). The Curious Case of Neural Text Degeneration. International Conference on Learning Representations. §11.1 §F.2
- (2020). Insight Into Insiders and IT. ACM Computing Surveys. §51.1 §53.5 §56.2 §56.6 §56.7 §D.19 §F.22
- (2020). The Ethics of AI and Robotics. Lexington Books. §16.7 §60.3 §F.20
- (1996). Mental and physical countermeasures reduce the accuracy of the concealed knowledge test. Psychophysiology. §39.4 §39.8 §F.34
- (2023). Towards Developmental Interpretability. AI Alignment Forum. non-peer-reviewed §10.2 §43.5 §F.14
- (2024). Loss Landscape Degeneracy and Stagewise Development in Transformers. Trans. Mach. Learn. Res.. §10.2 §F.2
- (2024). On the Limitations of Compute Thresholds as a Governance Strategy. arXiv. preprint §63.2 §63.3 §63.9 §66.5 §66.9 §F.13
- (2019). exBERT: A Visual Analysis Tool to Explore Learned Representations in Transformers Models. arXiv. preprint §F.7
- (1989). Multilayer feedforward networks are universal approximators. Neural Networks. §8.2 §F.2
- (2023). Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus? National Bureau of Economic Research. working paper §F.25
- (1999). Principles of mixed-initiative user interfaces. Proceedings of the SIGCHI conference on Human factors in computing systems the CHI is the limit - CHI '99. §60.5 Ch. 60 §F.31
- (2023). Human Feedback is not Gold Standard. arXiv. preprint §13.6 §18.3 §22.5 §22.6 §22.10 §30.4 §30.7 §F.38
- (2025). Winning the Race: America’s AI Action Plan. The White House. non-peer-reviewed §61.3 §63.2 §63.3 §63.7 §65.1 §F.13 §I.1
- (1966). Information Value Theory. IEEE Transactions on Systems Science and Cybernetics. §71.1 §F.40
- (2005). Influence Diagrams. Decision Analysis. §7.7 §14.7 §F.2
- (2025). Scaling Trends in Language Model Robustness. International Conference on Machine Learning. §5.8 §48.1 §48.9 Ch. 48 §F.8
- (2021). Decision-Focused Summarization. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2021.emnlp-main.10. §F.11
- (2019). Do Attention Heads in BERT Track Syntactic Dependencies? arXiv. preprint §F.2
- (2021). LoRA: Low-Rank Adaptation of Large Language Models. International Conference on Learning Representations. §F.2
- (2024). Amortizing intractable inference in large language models. International Conference on Learning Representations. §28.5 §F.4
- (2025). Understanding In-context Learning of Addition via Activation Subspaces. arXiv. preprint §F.7
- (2020). Retrieve, Program, Repeat: Complex Knowledge Base Question Answering via Alternate Meta-learning. International Joint Conference on Artificial Intelligence. doi:10.24963/ijcai.2020/505. §F.11
- (2025). Steering Evaluation-Aware Language Models to Act Like They Are Deployed. arXiv. preprint §37.4 §37.6 §37.10 §F.6
- (2025). Decomposing Representation Space into Interpretable Subspaces with Unsupervised Learning. arXiv. preprint §F.7
- (2022). Large Language Models Can Self-Improve. Conference on Empirical Methods in Natural Language Processing. §F.2
- (2023). A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions. ACM Trans. Inf. Syst.. doi:10.1145/3703155. §F.2
- (2024a). Collective Constitutional AI: Aligning a Language Model with Public Input. The 2024 ACM Conference on Fairness, Accountability, and Transparency. §1.7 §3.8 §17.7 §17.8 Ch. 17 §23.2 §23.6 §23.7 §23.8 §23.9 Ch. 23 §70.3 §F.42
- (2024b). Flames: Benchmarking Value Alignment of LLMs in Chinese. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). §36.4 §F.6
- (2024c). InversionView: A General-Purpose Method for Reading Information from Neural Activations. Advances in Neural Information Processing Systems. §F.7
- (2024d). MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation. International Conference on Machine Learning. §55.2 §F.8
- (2024e). RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations. Annual Meeting of the Association for Computational Linguistics. §F.7
- (2025a). Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization. International Conference on Learning Representations. §12.8 §15.4 §22.4 §F.2
- (2025b). Predictive Concept Decoders: Training Scalable End-to-End Interpretability Assistants. arXiv. preprint §46.7 §F.7
- (2025c). Values in the Wild: Discovering and Analyzing Values in Real-World Language Model Interactions. arXiv. preprint §18.1 §18.8 §18.10 §23.6 §26.5 §37.8 §F.4
- (1962). Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. The Journal of Physiology. §F.39
- (2002). Deliberate Discretion? Cambridge University Press. §61.1 §F.45
- (2019). Gradient hacking. AI Alignment Forum. non-peer-reviewed §24.6 §33.3 §F.14
- (2020). An overview of 11 proposals for building safe advanced AI. arXiv. preprint §3.1 §3.9 §31.6 §41.2 §F.5
- (2022). How likely is deceptive alignment? AI Alignment Forum. non-peer-reviewed §3.4 §9.3 §34.2 §34.10 §70.3 §F.14
- (2025). Alignment remains a hard, unsolved problem. AI Alignment Forum. non-peer-reviewed §3.8 §26.1 §31.7 §71.5 §F.14 §I.5
- (2019). Risks from Learned Optimization in Advanced Machine Learning Systems. arXiv. preprint §1.1 §2.4 §3.4 Ch. 3 §10.3 Ch. 10 §11.7 §26.1 Ch. 29 §29.1 §31.2 §31.6 Ch. 31 §33.1 §34.1 §34.2 §C.4 §F.5
- (2023). Conditioning Predictive Models: Risks and Strategies. arXiv. preprint §F.11
- (2024). Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training. arXiv. preprint §2.6 §3.4 §5.3 §5.7 §27.6 §34.3 §34.7 §34.10 Ch. 34 §38.5 §48.6 §C.6 §E.1 §E.3 §F.8
- (2024). Best-of-N Jailbreaking. arXiv. preprint §48.3 §48.5 §48.9 §70.3 §F.8
- (2025). Alignment Faking Revisited: Improved Classifiers and Open Source Extensions. Anthropic Alignment Science Blog. non-peer-reviewed §5.3 §5.7 §34.4 §E.3 §F.5
- (2024). The Platonic Representation Hypothesis. International Conference on Machine Learning. §39.7 §39.11 §42.7 §46.6 §46.9 Ch. 46 §F.7
- (2025). Large Language Models, Small Labor Market Effects. Elsevier BV. preprint §4.4 §68.5 §68.6 §68.8 §70.3 §F.25
- (1957). The Soldier and the State. Harvard University Press. §14.5 §51.3 §C.1 §D.2 §F.19
- (2008). Comparing Measures of Sparsity. IEEE Transactions on Information Theory. doi:10.1109/TIT.2009.2027527. §F.11
- (2008). But Who Will Guard the Guardians? American Economic Review. §14.5 §50.4 §F.25
- (2022). The Design of Mechanisms for Resource Allocation. The Collected Papers of Leonid Hurwicz. §F.25
- (2004). Universal Artificial Intelligence. Springer Berlin / Heidelberg. §7.6 §F.24
I
- (2023). The Integrated Information Theory of Consciousness as Pseudoscience. Center for Open Science. preprint §21.2 §F.44
- (2019). AI Safety, Security, and Stability Among Great Powers: Options, Challenges, and Lessons Learned for Pragmatic Engagement. Center for Security and Emerging Technology. non-peer-reviewed §66.3 §F.32
- (2023). Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations. arXiv. preprint §F.11
- (2000). Modernization, Cultural Change, and the Persistence of Traditional Values. American Sociological Review. §F.55
- (2014). Coverage is not strongly correlated with test suite effectiveness. Proceedings of the 36th International Conference on Software Engineering. §15.2 §24.2 §D.10 §F.50
- (2013). Procedures for the Preparation, Review, Acceptance, Adoption, Approval and Publication of IPCC Reports (Appendix A to the Principles Governing IPCC Work). non-peer-reviewed §66.6 §F.28
- (2013). Turkopticon. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. §F.12
- (2025). Fast weight programming and linear transformers: from machine learning to neurobiology. Trans. Mach. Learn. Res.. §F.9
- (2025). Consistency Training Helps Stop Sycophancy and Jailbreaks. arXiv. preprint §22.6 §22.10 §30.4 §70.3 §F.5
- (2018). AI safety via debate. arXiv. preprint §3.5 §3.8 §41.3 Ch. 41 §70.3 §C.4 §F.6
- (2025). AI with Emotions: Exploring Emotional Expressions in Large Language Models. Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities. §F.2
- (2020). Testing Measurement Invariance of the Moral Foundations Questionnaire Across 27 Countries. Assessment. §18.2 §F.48
- (2024). Principal-Agent Reinforcement Learning: Orchestrating AI Agents with Contracts. arXiv. preprint §14.8 §F.25
J
- (1995). Deriving specifications from requirements. Proceedings of the 17th international conference on Software engineering - ICSE '95. §30.3 §F.50
- (2005). Accountability, incentives and behavior: the impact of high-stakes testing in the Chicago Public Schools. Journal of Public Economics. §14.2 §15.2 §15.7 §26.6 §36.5 §53.1 §53.9 §F.48 §H.3
- (2003). Rotten Apples: An Investigation of the Prevalence and Predictors of Teacher Cheating. The Quarterly Journal of Economics. §14.2 §15.2 §F.25
- (2021). Measurement and Fairness. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. §F.55
- (1991). Adaptive Mixtures of Local Experts. Neural Computation. §F.11
- (2025). Block-Recurrent Dynamics in Vision Transformers. arXiv. preprint §F.2
- (2020). Towards Faithfully Interpretable NLP Systems: How Should We Define and Evaluate Faithfulness? Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. §40.3 §43.1 §46.7 §47.2 §F.7
- (2025). RelP: Faithful and Efficient Circuit Discovery in Language Models via Relevance Patching. arXiv. preprint §F.7
- (1997). Catastrophe Insurance, Capital Markets, and Uninsurable Risks. The Journal of Risk and Insurance. §63.5 §63.9 §D.5 §F.27
- (2026). Reinforcement Learning Towards Broadly and Persistently Beneficial Models. arXiv. preprint §23.5 §23.9 §24.7 §24.8 §24.9 §26.2 §26.8 §32.7 §E.5 §F.5
- (2019). On the "steerability" of generative adversarial networks. International Conference on Learning Representations. §F.8
- (2019). Attention is not Explanation. North American Chapter of the Association for Computational Linguistics. doi:10.18653/v1/N19-1357. §F.2
- (2023). Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks. arXiv. preprint §F.7
- (2026). Exploration Hacking: Can LLMs Learn to Resist RL Training? International Conference on Machine Learning. §24.6 §33.3 §33.4 §34.5 §36.2 §70.3 §F.5
- (2024). Characterizing stable regions in the residual stream of LLMs. arXiv. preprint §F.4
- (2022). Simulators. AI Alignment Forum. non-peer-reviewed §1.6 §2.8 §3.4 §3.10 §11.6 Ch. 11 §26.1 §69.5 §70.3 §C.5 §F.14
- (2017). Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control. International Conference on Machine Learning. §12.2 §22.3 §F.2
- (2024). Uncovering Deceptive Tendencies in Language Models: A Simulated Company AI Assistant. arXiv. preprint §34.5 §F.5
- (2003). Technologies of Humility: Citizen Participation in Governing Science. Minerva. §17.6 §F.45
- (2015). CRISPR Democracy: Gene Editing and the Need for Inclusive Deliberation. Issues in Science and Technology. non-peer-reviewed §2.1 §2.7 §2.10 §17.6 §64.2 §64.10 §F.30
- (1965). The Logic of Decision. University Of Chicago Press. §7.6 §F.24
- (2024). Evidence of Learned Look-Ahead in a Chess-Playing Neural Network. Advances in Neural Information Processing Systems. doi:10.52202/079017-0987. §10.3 §31.6 §45.2 §F.5
- (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics. §1.3 §14.1 §61.1 Ch. 61 §C.2 §D.1 §F.25
- (2020). Reward-rational (implicit) choice: A unifying formalism for reward learning. Advances in Neural Information Processing Systems. §13.2 §13.3 §22.1 §F.2
- (2022). Engineering Monosemanticity in Toy Models. arXiv. preprint §44.3 §F.7
- (1978). Cooperation under the Security Dilemma. World Politics. §65.3 Ch. 65 §D.2 §F.32
- (2017). Perception and Misperception in International Politics. Princeton University Press. §65.3 §F.32
- (2023). AI Alignment: A Comprehensive Survey. arXiv. preprint §2.1 §2.8 §3.1 §22.8 §F.4
- (2025). Language Models Resist Alignment: Evidence From Data Compression. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). §6.2 §26.4 §26.9 §27.1 §F.2
- (2025). Language Models Are Capable of Metacognitive Monitoring and Control of Their Internal Activations. Neural Information Processing Systems. §F.7
- (2020). Fantastic Generalization Measures and Where to Find Them. International Conference on Learning Representations. §9.1 §10.2 §F.2
- (2021). Can Machines Learn Morality? The Delphi Experiment. arXiv. preprint §16.1 §16.11 §F.3
- (2023a). Evaluating and Inducing Personality in Pre-trained Language Models. Advances in Neural Information Processing Systems. §26.5 §F.4
- (2023b). Mistral 7B. arXiv. preprint §F.11
- (2024a). Devils in Middle Layers of Large Vision-Language Models: Interpreting, Detecting and Mitigating Object Hallucinations via Attention Lens. Computer Vision and Pattern Recognition. doi:10.1109/CVPR52734.2025.02328. §F.2
- (2024b). Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations. International Conference on Learning Representations. §F.7
- (2023). SWE-bench: Can Language Models Resolve Real-World GitHub Issues? International Conference on Learning Representations. §11.5 §F.2
- (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence. §2.5 §16.5 §C.4 §F.55
- (2025). Training LLMs for Honesty via Confessions. arXiv. preprint §39.9 §39.10 §39.11 §39.12 Ch. 39 §40.6 §E.5 §F.6
- (1984). Extensions of Lipschitz mappings into a Hilbert space. Contemporary Mathematics. §44.2 §F.7
- (2013). Abrupt rise of new machine ecology beyond human response time. Scientific Reports. §54.2 §57.4 §57.9 §F.21
- (2025). The California Report on Frontier AI Policy. Office of the Governor of California. non-peer-reviewed §63.2 §67.4 §F.13
- (2017). Could a Neuroscientist Understand a Microprocessor? PLOS Computational Biology. §43.6 Ch. 43 §47.7 §D.15 §F.39
- (2024). The AI Dilemma: Growth versus Existential Risk. American Economic Review: Insights. §4.6 §68.5 §F.25
- (1971). The bogus pipeline: A new paradigm for measuring affect and attitude. Psychological Bulletin. §F.47
- (2023). Automatically Auditing Large Language Models via Discrete Optimization. International Conference on Machine Learning. §38.3 §F.6
- (2024). Adversaries Can Misuse Combinations of Safe Models. International Conference on Machine Learning. §59.3 §59.8 §70.1 §F.9
- (2025). Forecasting Rare Language Model Behaviors. arXiv. preprint §6.6 §36.7 §48.3 §E.1 §E.3 §F.8
- (1988). Abuse of Casuistry. University of California Press. §19.4 §F.20
- (2025). Reasoning Models Sometimes Output Illegible Chains of Thought. Neural Information Processing Systems. §40.2 §40.8 §70.3 §F.6
- (2017). TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/P17-1147. §F.11
- (2020). The State and Fate of Linguistic Diversity and Inclusion in the NLP World. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. §17.4 §27.3 §36.4 §F.4
- (2024). Personas as a Way to Model Truthfulness in Language Models. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. §26.3 §26.4 §26.9 §32.7 §39.1 §F.5
- (2026). MonitoringBench: Semi-Automated Red-Teaming for Agent Monitoring. arXiv. preprint §F.6
- (2016). FastText.zip: Compressing text classification models. arXiv. preprint §F.11
- (2022). Linear Connectivity Reveals Generalization Strategies. International Conference on Learning Representations. §F.2
- (1988). Disclosure When the Market Is Unsure of Information Endowment of Managers. Journal of Accounting Research. §54.6 §F.25
K
- (2022). Language Models (Mostly) Know What They Know. arXiv. preprint §6.4 Ch. 6 §20.2 §E.1 §E.3 §F.2
- (2009). Conditions for intuitive expertise: A failure to disagree. American Psychologist. §4.5 §18.3 §F.28
- (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica. §7.2 §13.3 §13.6 §F.25
- (1997). Back to Bentham? Explorations of Experienced Utility. The Quarterly Journal of Economics. §13.1 §F.25
- (2025). Why Language Models Hallucinate. arXiv. preprint §6.4 §39.2 §39.11 §39.12 §F.2
- (2025). Reliable Weak-to-Strong Monitoring of LLM Agents. arXiv. preprint §42.6 §50.3 §50.5 §50.6 §51.2 §69.4 §F.8 §H.2
- (1959). On the general theory of control systems. IRE Transactions on Automatic Control. §F.21
- (2016). Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability? Transportation Research Part A: Policy and Practice. §6.5 §52.1 §52.8 §59.6 §F.8 §H.3
- (2025). Tracing Attention Computation Through Feature Interactions. Transformer Circuits Thread. non-peer-reviewed §45.4 §E.4 §F.7
- (2011). Bayesian Persuasion. American Economic Review. §14.1 §39.2 §60.2 §F.25
- (2013). Validating the Interpretations and Uses of Test Scores. Journal of Educational Measurement. §36.8 §52.2 §F.48
- (2025). Language Models Use Trigonometry to Do Addition. arXiv. preprint §F.2
- (2025). Are Sparse Autoencoders Useful? A Case Study in Sparse Probing. International Conference on Machine Learning. §3.6 §44.7 §44.8 Ch. 44 §47.7 §F.7
- (1981). On The Quantitative Definition of Risk. Risk Analysis. §4.2 §52.4 §D.7 §F.51
- (2020). Scaling Laws for Neural Language Models. arXiv. preprint §2.4 §6.2 §8.3 §8.5 Ch. 8 §9.2 §C.5 §F.2
- (1992). Rules versus Standards: An Economic Analysis. Duke Law Journal. §19.4 §19.9 Ch. 19 §23.3 Ch. 23 §D.3 §F.33
- (2024). AI Snake Oil. Princeton University Press. §F.43
- (2024a). AI Agents That Matter. arXiv. preprint §36.3 §F.6
- (2024b). On the Societal Impact of Open Foundation Models. arXiv. preprint §3.8 §3.10 §38.8 §48.4 §48.7 §58.6 §59.1 §59.2 §59.4 §59.8 Ch. 59 §63.7 §63.9 Ch. 63 §67.6 §70.3 §F.13
- (2012). Optimal control as a graphical model inference problem. Machine Learning. §12.4 §F.2
- (2003). Multics security evaluation: vulnerability analysis. 18th Annual Computer Security Applications Conference, 2002. Proceedings.. §58.7 §64.7 §F.22
- (2023). Forecasting Existential Risks: Evidence from a Long-Run Forecasting Tournament. Forecasting Research Institute, Working Paper #1. working paper §4.4 §4.5 §4.6 §4.8 Ch. 4 §70.6 §F.43 §H.3
- (2024). ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities. arXiv. preprint §4.5 §F.28
- (2025). Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament. International Journal of Forecasting. §4.5 §F.28
- (2015). Visualizing and Understanding Recurrent Networks. arXiv. preprint §F.11
- (2024). Evaluating Sparse Autoencoders on Targeted Concept Erasure Tasks. arXiv. preprint §44.6 §44.7 §44.8 §F.7
- (2025). Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers. arXiv. preprint §43.7 §46.7 §46.9 §E.3 §E.4 §F.7
- (2026). Would this change your answer? Evaluating Explanations of LLM Behavior In The Wild with Counterfactual Experiments. arXiv. preprint §E.3 §F.58
- (2023). Goodhart's Law in Reinforcement Learning. International Conference on Learning Representations. §15.4 §F.2
- (2025). Two types of AI existential risk: decisive and accumulative. Philosophical Studies. §4.1 §68.6 §F.42
- (2023). In Conversation with Artificial Intelligence: Aligning language Models with Human Values. Philosophy & Technology. §16.8 §19.5 §20.2 §D.18 §F.55
- (2023). VISIT: Visualizing and Interpreting the Semantic Information Flow of Transformers. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2023.findings-emnlp.939. §F.2
- (2017). Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks. Lecture Notes in Computer Science. §28.6 §48.6 §F.24
- (2024). Backward Lens: Projecting Language Model Gradients into the Vocabulary Space. Conference on Empirical Methods in Natural Language Processing. §F.2
- (2024). The Manhattan Trap: Why a Race to Artificial Superintelligence is Self-Defeating. arXiv. preprint §65.2 §65.3 §65.5 §65.6 §65.8 §F.29
- (1960). The Forest Ranger. Routledge. §19.6 §25.7 §D.4 §F.46
- (2026). Aligned, Orthogonal or In-conflict: When can we safely optimize Chain-of-Thought? arXiv. preprint §24.3 §24.7 §40.1 §40.2 §40.6 §40.8 §70.3 §F.4 §H.2
- (2024). Can LLMs make trade-offs involving stipulated pain and pleasure states? arXiv. preprint §21.4 §21.5 §21.9 §F.44
- (2020). Algorithms at Work: The New Contested Terrain of Control. Academy of Management Annals. §51.3 §F.54
- (1997). Safety Case Construction and Reuse Using Patterns. Safe Comp 97. §52.2 §F.51
- (1958). Compliance, identification, and internalization three processes of attitude change. Journal of Conflict Resolution. §25.1 Ch. 25 §C.1 §D.11 §F.57
- (1989). Crimes of Obedience: Toward a Social Psychology of Authority and Responsibility. Yale University Press. §F.47
- (1979). The Need for Change, the Legacy of TMI: Report of the President's Commission on the Accident at Three Mile Island. Pergamon Press. non-peer-reviewed §64.3 §F.51
- (2021). Alignment of Language Agents. arXiv. preprint §1.1 §20.2 §20.9 §F.42
- (2023). Discovering agents. Artificial Intelligence. §1.5 §7.1 §14.8 §F.24
- (2024). On scalable oversight with weak LLMs judging strong LLMs. Advances in Neural Information Processing Systems. §41.5 §41.9 §41.10 §F.6 §H.5
- (2026). Debate Training Reduces Reward Hacking in RLAIF. arXiv. preprint §F.6
- (1984). After Hegemony: Cooperation and Discord in the World Political Economy. Princeton University Press. §66.2 §F.32
- (2011). The Regime Complex for Climate Change. Perspectives on Politics. §66.7 §66.9 §F.32
- (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character. §49.7 §F.36
- (1975). On the Folly of Rewarding A, While Hoping for B. Academy of Management Journal. §14.2 §15.2 §18.5 §22.7 §25.6 §25.7 Ch. 25 §53.1 §C.2 §D.4 §F.25
- (2000). Is Hospital Competition Socially Wasteful? The Quarterly Journal of Economics. §F.25
- (2026). Countdown-Code: A Testbed for Studying The Emergence and Generalization of Reward Hacking in RLVR. arXiv. preprint §F.5
- (2024). Debating with More Persuasive LLMs Leads to More Truthful Answers. International Conference on Machine Learning. §41.5 §41.10 §42.7 §F.6 §H.5
- (2025). Randomness, Not Representation: The Unreliability of Evaluating Cultural Alignment in LLMs. Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency. §1.5 §1.8 §5.5 §5.9 §7.3 §17.4 §17.8 §18.7 §18.8 §18.10 Ch. 18 §26.5 §26.6 §26.9 §69.5 §70.3 §F.2 §H.2
- (2017). Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV). International Conference on Machine Learning. §F.7
- (2025). Kimi k1.5: Scaling Reinforcement Learning with LLMs. arXiv. preprint §12.7 §24.1 §24.9 §F.2
- (2017a). Learning how to explain neural networks: PatternNet and PatternAttribution. International Conference on Learning Representations. §F.7
- (2017b). The (Un)reliability of saliency methods. Explainable AI. doi:10.1007/978-3-030-28954-6_14. §43.3 §43.8 §F.7
- (2014). Adam: A Method for Stochastic Optimization. International Conference on Learning Representations. §8.3 §F.2
- (2023). Evaluating Language-Model Agents on Realistic Autonomous Tasks. arXiv. preprint §F.6
- (2024). Prover-Verifier Games improve legibility of LLM outputs. arXiv. preprint §3.5 §41.5 §41.10 §41.11 §F.6
- (2025). AbstentionBench: Reasoning LLMs Fail on Unanswerable Questions. Neural Information Processing Systems. §F.11
- (2017). The Flash Crash: High‐Frequency Trading in an Electronic Market. The Journal of Finance. §57.4 §F.21
- (2024a). The benefits, risks and bounds of personalizing the alignment of large language models to individuals. Nature Machine Intelligence. §17.2 §F.42
- (2024b). The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models. Advances in Neural Information Processing Systems. §17.2 §17.7 §22.7 §F.42
- (2025). Why human–AI relationships need socioaffective alignment. Humanities and Social Sciences Communications. §60.3 §F.31
- (2024). Interpreting Attention Layer Outputs with Sparse Autoencoders. arXiv. preprint §F.7
- (2005). At the Margins of Moral Personhood. Ethics. §21.6 §F.42
- (2000). What Do Test Scores in Texas Tell Us? RAND Corporation. §15.7 §36.5 Ch. 36 §D.12 §F.48
- (2020). How Do Classifiers Induce Agents to Invest Effort Strategically? ACM Transactions on Economics and Computation. §14.2 §15.1 §15.7 §36.5 §F.25
- (2016). Inherent Trade-Offs in the Fair Determination of Risk Scores. arXiv. preprint §17.3 §17.8 §F.12 §H.1
- (2023). The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization. Management Science. §13.1 §60.2 §F.31
- (2024). What are human values, and how do we align AI to them? arXiv. preprint §17.2 §17.5 §17.7 §17.8 §70.3 §F.42
- (1986). An experimental evaluation of the assumption of independence in multiversion programming. IEEE Transactions on Software Engineering. §6.7 §50.4 §50.6 Ch. 50 §52.3 §52.8 Ch. 52 §57.4 Ch. 57 §C.2 §D.8 §F.8
- (2022). Models of human preference for learning reward functions. arXiv. preprint §13.3 §22.5 §F.2
- (2020). Attention is Not Only a Weight: Analyzing Transformers with Vector Norms. arXiv. preprint §F.2
- (1995). Mother-Child Mutually Positive Affect, the Quality of Child Compliance to Requests and Prohibitions, and Maternal Control as Correlates of Early Internalization. Child Development. §25.2 §F.57
- (2023). Risk assessment at AGI companies: A review of popular risk assessment techniques from other safety-critical industries. arXiv. preprint §F.8
- (2024). Risk thresholds for frontier AI. arXiv. preprint Ch. 62 §62.3 §62.9 §70.3 §F.13
- (2017). Understanding Black-box Predictions via Influence Functions. International Conference on Machine Learning. §10.1 §F.2
- (2022). Large Language Models are Zero-Shot Reasoners. Advances in Neural Information Processing Systems. doi:10.52202/068431-1613. §F.2
- (2021). Investigating sanity checks for saliency maps with image and text classification. arXiv. preprint §43.3 §43.8 §F.7
- (2025). AI 2027. AI Futures Project (ai-2027.com). non-peer-reviewed §4.3 §65.5 §F.25
- (2003). Multi-agent influence diagrams for representing and solving games. Games and Economic Behavior. §14.7 §57.2 §F.9
- (2019). Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs. Computer Vision and Pattern Recognition. doi:10.1109/CVPR42600.2020.00038. §F.8
- (2024). Governing AI Agents. Elsevier BV. preprint §1.4 §56.8 Ch. 56 §F.33
- (2024). Responsible Reporting for Frontier AI Development. arXiv. preprint §54.6 §67.4 §F.13
- (2019). A Safety Standard Approach for Fully Autonomous Vehicles. Lecture Notes in Computer Science. §59.6 §F.51
- (2022). RL with KL penalties is better viewed as Bayesian inference. Findings of the Association for Computational Linguistics: EMNLP 2022. doi:10.18653/v1/2022.findings-emnlp.77. §3.3 §6.1 §12.2 §12.4 Ch. 12 §26.1 §F.2
- (2023). Pretraining Language Models with Human Preferences. International Conference on Machine Learning. §27.2 §F.4
- (2025a). A sketch of an AI control safety case. arXiv. preprint §52.2 §52.5 §52.8 §F.8
- (2025b). Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety. arXiv. preprint §3.5 §4.7 §40.1 §40.2 §40.6 §40.8 Ch. 40 §52.5 §70.3 §C.7 §F.8 §H.2
- (2025c). How to evaluate control measures for LLM agents? A trajectory from today to superintelligence. arXiv. preprint §3.7 §50.2 §50.6 Ch. 50 §51.4 §51.6 §52.5 §52.8 Ch. 52 §70.3 §F.8
- (2026). How far does alignment midtraining generalize? OpenAI Alignment Research Blog. non-peer-reviewed §23.5 §23.8 §23.9 §27.4 §27.9 §32.7 §70.3 §E.5 §F.5
- (2025). Framework Act on the Development of Artificial Intelligence and Establishment of Trust. Center for Security and Emerging Technology (translation). non-peer-reviewed §63.2 §F.33 §I.1
- (2001). The Rational Design of International Institutions. International Organization. §66.2 §66.7 §F.32
- (2008). Measuring Up. Harvard University Press. §15.7 §D.12 §F.48
- (2017). The Testing Charade. University of Chicago Press. §15.7 §F.48
- (2016). Auditing for Score Inflation Using Self-Monitoring Assessments: Findings From Three Pilot Studies. Educational Assessment. §15.7 §36.5 §D.12 §F.48
- (2023). Aligned with Whom? The Oxford Handbook of AI Governance. §1.4 Ch. 1 §14.4 §20.3 §56.1 Ch. 59 §61.3 §68.1 Ch. 68 §69.5 §F.25
- (2019). Artificial Intelligence and Its Implications for Income Distribution and Unemployment. The Economics of Artificial Intelligence. §68.3 §68.5 §F.25
- (2024). Scenarios for the Transition to AGI. National Bureau of Economic Research. working paper §68.5 §F.25
- (2024). Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence. National Bureau of Economic Research. non-peer-reviewed §65.5 §68.3 §F.25
- (1996). The Sources of Normativity. Cambridge University Press. §16.1 §F.42
- (2011). Stackelberg vs. Nash in Security Games: An Extended Investigation of Interchangeability, Equivalence, and Uniqueness. Journal of Artificial Intelligence Research. §14.6 §F.40
- (2025). Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task. arXiv. preprint §F.39
- (2019). Revealing the Dark Secrets of BERT. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/D19-1445. §F.11
- (2025). It's the Thought that Counts: Evaluating the Attempts of Frontier LLMs to Persuade on Harmful Topics. arXiv. preprint §36.1 §36.6 §36.10 §60.3 §F.9
- (2023). Building transformers from neurons and astrocytes. Proceedings of the National Academy of Sciences. §F.7
- (1986). Gatekeepers: The Anatomy of a Third-Party Enforcement Strategy. The Journal of Law, Economics, and Organization. §67.2 §D.5 §F.33
- (2017). Neuroscience Needs Behavior: Correcting a Reductionist Bias. Neuron. §43.6 §F.39
- (2018). Specification gaming examples in AI. Victoria Krakovna (personal blog), with linked public spreadsheet. non-peer-reviewed §30.1 §F.5
- (2023). Power-seeking can be probable and predictive for trained agents. arXiv. preprint §31.2 §35.2 §35.3 §35.8 §F.24 §H.1
- (2018). Penalizing side effects using stepwise relative reachability. arXiv. preprint §28.2 §28.3 §28.9 Ch. 28 §35.6 §F.24
- (2020a). Avoiding Side Effects By Considering Future Tasks. Advances in Neural Information Processing Systems. §28.3 §28.9 §F.4
- (2020b). Specification gaming: the flip side of AI ingenuity. Google DeepMind blog. non-peer-reviewed §1.3 §2.4 §2.8 §3.3 §15.3 §22.6 §30.1 Ch. 30 §31.1 §C.5 §F.5
- (2022). Refining the Sharp Left Turn threat model, part 1: claims and mechanisms. AI Alignment Forum. non-peer-reviewed §4.7 §31.7 §F.14
- (2024). AtP*: An efficient and scalable method for localizing LLM behaviour to components. arXiv. preprint §43.3 §43.9 §F.7
- (2023). Implicit meta-learning may lead language models to trust more reliable sources. International Conference on Machine Learning. §F.2
- (2025). Liars' Bench: Evaluating Lie Detectors for Language Models. arXiv. preprint §39.1 §39.5 §39.6 §39.9 §39.10 §39.11 §F.6 §H.2
- (2008). Representational similarity analysis – connecting the branches of systems neuroscience. Frontiers in Systems Neuroscience. §F.39
- (1982). Genetic Alchemy: The Social History of the Recombinant DNA Controversy. §2.7 §64.1 §F.30
- (2026). LatentLens: Revealing Highly Interpretable Visual Tokens in LLMs. arXiv. preprint §F.7
- (2020). Large Associative Memory Problem in Neurobiology and Machine Learning. International Conference on Learning Representations. §F.9
- (2016). Indigenous Data Sovereignty. ANU Press. §17.4 §27.3 §F.12
- (1951). On Information and Sufficiency. The Annals of Mathematical Statistics. §6.3 Ch. 6 §F.56
- (2024). Hardware-Enabled Governance Mechanisms: Developing Technical Solutions to Exempt Items Otherwise Classified Under Export Control Classification Numbers 3A090 and 4A090. RAND Corporation, WR-A3056-1. working paper §66.5 §F.13
- (2025). Gradual Disempowerment: Systemic Existential Risks from Incremental AI Development. arXiv. preprint §4.1 §60.6 Ch. 68 §68.1 §68.2 §68.4 §68.5 §68.6 §68.8 Ch. 68 §69.3 §70.3 §F.45
- (2024). Refusal-Trained LLMs Are Easily Jailbroken As Browser Agents. arXiv. preprint §F.9
- (2023). Specific versus General Principles for Constitutional AI. arXiv. preprint §3.3 §23.2 §23.6 §23.7 §23.8 §23.9 Ch. 23 §70.3 §E.1 §E.3 §F.4
- (2019). Loss Landscapes of Regularized Linear Autoencoders. International Conference on Machine Learning. §F.11
- (1993). Insurer ambiguity and market failure. Journal of Risk and Uncertainty. §63.5 §D.5 §F.27
- (2019). Limitations of the Empirical Fisher Approximation for Natural Gradient Descent. Advances in Neural Information Processing Systems. §F.11
- (2025). OS-Harm: A Benchmark for Measuring Safety of Computer Use Agents. Advances in Neural Information Processing Systems 38. §49.3 §56.3 §F.8
- (2025a). Evaluating Control Protocols for Untrusted AI Agents. arXiv. preprint §50.3 §50.5 §50.6 §F.8
- (2025b). SHADE-Arena: Evaluating Sabotage and Monitoring in LLM Agents. arXiv. preprint §34.5 §40.6 §50.3 §56.3 §E.1 §F.8
- (2024). Catastrophic Goodhart: regularizing RLHF with KL divergence does not mitigate heavy-tailed reward misspecification. Advances in Neural Information Processing Systems. doi:10.52202/079017-0466. §4.6 §12.8 §15.5 §15.6 Ch. 15 §22.5 §30.2 Ch. 30 §F.5
- (2025). Measuring AI Ability to Complete Long Software Tasks. Advances in Neural Information Processing Systems 38. §3.7 §4.3 §5.8 §8.6 §11.5 §36.1 §36.2 §36.3 §36.4 §36.7 §36.10 Ch. 36 §F.2 §H.2
- (2023). Efficient Memory Management for Large Language Model Serving with PagedAttention. Symposium on Operating Systems Principles. doi:10.1145/3600006.3613165. §F.2
- (1977). Rules Rather than Discretion: The Inconsistency of Optimal Plans. Journal of Political Economy. §61.5 §F.25
L
- (1991). Working in Practice But Not in Theory: Theoretical Challenges of “High-Reliability Organizations”. Journal of Public Administration Research and Theory. §53.2 §53.9 Ch. 53 §F.41
- (2025). Helpful assistant features suppress emergent misalignment. OpenAI Alignment Research Blog. non-peer-reviewed §26.3 §32.3 §32.8 §E.5 §F.5
- (2025). Debugging misaligned completions with sparse-autoencoder latent attribution. OpenAI Alignment Research Blog. non-peer-reviewed §32.3 §E.5 §F.5
- (2024). The Remarkable Robustness of LLMs: Stages of Inference? arXiv. preprint §F.8
- (2026). The Misery of Mechanistic Interpretability: A Formal Perspective. arXiv. preprint §47.3 §47.8 §F.7
- (2024). Too human and not human enough: A grounded theory analysis of mental health harms from emotional dependence on the social chatbot Replika. New Media & Society. §60.3 §F.31
- (1991). The Politics of Government Decision-Making: A Theory of Regulatory Capture. The Quarterly Journal of Economics. §61.6 §63.3 §F.49
- (2019). Democracy without Shortcuts. Oxford University PressOxford. §17.7 §17.8 §70.3 §F.45
- (2024). Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs. Advances in Neural Information Processing Systems. §3.4 §37.1 §37.10 Ch. 37 §F.6
- (1970). Falsification and the Methodology of Scientific Research Programmes. Criticism and the Growth of Knowledge. §3.8 §69.1 §F.37
- (2016). Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles. Advances in Neural Information Processing Systems. §6.4 §8.4 §F.2
- (2024). Tulu 3: Pushing Frontiers in Open Language Model Post-Training. arXiv. preprint §11.4 §12.6 §12.7 §22.3 §24.1 §F.2
- (2025). RewardBench: Evaluating Reward Models for Language Modeling. Findings of the Association for Computational Linguistics: NAACL 2025. §22.5 §22.9 §F.4
- (2026). Narrow Secret Loyalty Dodges Black-Box Audits. arXiv. preprint §38.2 §38.5 §38.7 §38.8 §38.10 §38.11 §51.1 §53.5 §53.9 §F.45
- (2006). Towards a true neural stance on consciousness. Trends in Cognitive Sciences. §F.11
- (2000). The distinct modes of vision offered by feedforward and recurrent processing. Trends in Neurosciences. §F.11
- (1982). The Byzantine Generals Problem. ACM Transactions on Programming Languages and Systems. §50.4 Ch. 50 §57.4 §D.8 §F.26
- (1973). A note on the confinement problem. Communications of the ACM. §24.6 Ch. 24 §40.5 §49.6 §51.1 §F.22
- (2024). Quantifying Feature Space Universality Across Large Language Models via Sparse Autoencoders. arXiv. preprint §46.6 §F.7
- (1983). The Measurement of Selection on Correlated Characters. Evolution. §32.6 §F.17
- (2019). Adopt a moratorium on heritable genome editing. Nature. §64.2 §64.8 §F.43
- (2024a). Theoretical Analysis of Weak-to-Strong Generalization. Advances in Neural Information Processing Systems. doi:10.52202/079017-1486. §42.2 §42.6 §42.8 Ch. 42 §F.6 §H.1
- (2024b). When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback. Advances in Neural Information Processing Systems. §18.3 §22.4 §22.6 §22.10 Ch. 22 §25.3 §30.4 §39.2 §42.6 §70.3 §F.5 §H.1
- (2025). Debate Helps Weak-to-Strong Generalization. arXiv. preprint §41.5 §42.3 §42.7 §42.8 §42.9 §F.6
- (2025). Common Corpus: The Largest Collection of Ethical Data for LLM Pre-Training. International Conference on Learning Representations. §27.1 §27.3 §F.4
- (2021). How RL Agents Behave When Their Actions Are Modified. Proceedings of the AAAI Conference on Artificial Intelligence. doi:10.1609/aaai.v35i13.17378. §14.7 §28.2 §35.3 §35.4 §F.5
- (1963). The Surveillance of Communicable Diseases of National Importance. New England Journal of Medicine. §54.2 §D.17 §F.36
- (2022). Goal Misgeneralization in Deep Reinforcement Learning. International Conference on Machine Learning. §1.1 §1.8 §3.4 Ch. 31 §31.1 §31.2 §31.3 §31.4 §31.6 §31.9 Ch. 31 §C.5 §F.5 §H.2
- (2023). Measuring Faithfulness in Chain-of-Thought Reasoning. arXiv. preprint §40.3 §40.8 Ch. 40 §E.1 §E.3 §F.6
- (2019). Unmasking Clever Hans predictors and assessing what machines really learn. Nature Communications. §8.4 §31.4 §36.6 §43.3 §F.15
- (2020). Good and bad reasons: The Swiss cheese model and its critics. Safety Science. §52.3 §F.51
- (2023). The Local Learning Coefficient: A Singularity-Aware Complexity Measure. arXiv. preprint §10.2 Ch. 10 §F.2
- (1986). Demonstrability and social combination processes on mathematical intellective tasks. Journal of Experimental Social Psychology. §F.53
- (2024). LAB-Bench: Measuring Capabilities of Language Models for Biology Research. arXiv. preprint §59.2 §F.9
- (2024). Residual Stream Analysis with Multi-Layer SAEs. International Conference on Learning Representations. §F.11
- (2023). AI safety on whose terms? Science. §1.4 §2.5 §2.9 §2.10 Ch. 2 §3.8 §4.4 Ch. 4 §16.8 §17.3 Ch. 17 §61.6 §61.8 §70.7 §C.6 §D.20 §F.45
- (2002). Can a biologist fix a radio?—Or, what I learned while studying apoptosis. Cancer Cell. §43.6 §F.39
- (2024). Learning biologically relevant features in a pathology foundation model using sparse autoencoders. arXiv. preprint §F.7
- (2025). Sparse Autoencoders Do Not Find Canonical Units of Analysis. International Conference on Learning Representations. §44.6 §44.8 §F.7 §H.2
- (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE. §F.11
- (2026). ExploitBench: A Capability Ladder Benchmark for LLM Cybersecurity Agents. arXiv. preprint §58.3 §58.10 §F.9
- (2018). Judging Ordinary Meaning. Yale Law Journal, Volume 127. non-peer-reviewed §19.4 §19.5 §F.35
- (2004). Trust in Automation: Designing for Appropriate Reliance. Human Factors: The Journal of the Human Factors and Ergonomics Society. §41.8 §41.10 §60.4 §60.5 §60.10 Ch. 60 §C.3 §D.13 §F.31 §H.3
- (2024). Prompt Infection: LLM-to-LLM Prompt Injection within Multi-Agent Systems. arXiv. preprint §49.7 §57.6 §57.7 §57.9 §F.8 §H.2
- (2022). Surgical Fine-Tuning Improves Adaptation to Distribution Shifts. International Conference on Learning Representations. §F.4
- (2023). RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback. International Conference on Machine Learning. §18.5 §22.7 §22.10 §23.2 §23.9 §F.4
- (2024). A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity. International Conference on Machine Learning. §22.4 §F.4
- (2025). Distillation Robustifies Unlearning. Neural Information Processing Systems. §27.5 §27.7 §27.9 §F.4
- (2026). Training Agents to Self-Report Misbehavior. arXiv. preprint §39.9 §39.10 §E.5 §F.6
- (2022). A New Generation of Perspective API: Efficient Multilingual Character-level Transformers. Knowledge Discovery and Data Mining. doi:10.1145/3534678.3539147. §20.3 §F.3
- (2024). SB-1047 Safe and Secure Innovation for Frontier Artificial Intelligence Models Act. California Legislative Information (enrolled 09/03/24; vetoed). non-peer-reviewed §63.2 §F.13
- (2025a). Responsible AI Safety and Education Act (New York RAISE Act). non-peer-reviewed §63.2 §F.13 §I.1
- (2025b). SB-53 Artificial intelligence models: large developers. California Legislative Information (chaptered 09/29/25). non-peer-reviewed §2.7 §53.4 §53.6 §54.6 §61.4 §61.5 Ch. 62 §62.3 §62.4 §62.5 §63.2 §63.3 §63.6 §63.7 §67.4 §C.7 §F.13 §I.1
- (2026). Transparency and safety requirements for developers of artificial intelligence frontier models (New York Laws of 2026, Chapter 96). non-peer-reviewed §63.1 §63.2 §63.3 §63.6 §63.7 §F.13 §I.1
- (2011). Abandoning Objectives: Evolution Through the Search for Novelty Alone. Evolutionary Computation. §29.2 §F.4
- (2020). The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities. Artificial Life. §2.4 §29.1 §30.1 §30.7 §C.4 §F.5 §H.2
- (2017). Multi-agent Reinforcement Learning in Sequential Social Dilemmas. International Joint Conference on Autonomous Agents and Multiagent Systems. §57.5 §F.9
- (1977). How does selection reconcile individual advantage with the good of the group? Proceedings of the National Academy of Sciences. §29.7 §F.17
- (2024). Crisp and fuzzy tasks. Musings on the Alignment Problem. non-peer-reviewed §55.1 §F.14
- (2023). Introducing Superalignment. OpenAI. non-peer-reviewed Ch. 55 §F.14
- (2017). AI Safety Gridworlds. arXiv. preprint §2.4 §3.3 §30.1 §F.5
- (2018). Scalable agent alignment via reward modeling: a research direction. arXiv. preprint §2.4 §3.5 §22.3 Ch. 22 §41.2 §41.3 §C.4 §F.4
- (2023). Uncovering Intermediate Variables in Transformers using Circuit Probing. arXiv. preprint §F.7
- (1973). Undermining children's intrinsic interest with extrinsic reward: A test of the "overjustification" hypothesis. Journal of Personality and Social Psychology. §25.3 §33.2 §C.2 §D.11 §F.57
- (1999). Code: and other laws of cyberspace. Basic Books. §17.5 §64.7 §F.33
- (2021). The Power of Scale for Parameter-Efficient Prompt Tuning. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2021.emnlp-main.243. §F.11
- (2017). Self unbound: ego dissolution in psychedelic experience. Neuroscience of Consciousness. §F.11
- (2016). The Economics of Disclosure and Financial Reporting Regulation: Evidence and Suggestions for Future Research. Journal of Accounting Research. §67.3 §67.4 §67.8 §F.49
- (2000). Intent specifications: an approach to building human-centered specifications. IEEE Transactions on Software Engineering. §F.50
- (2004). A new accident model for engineering safer systems. Safety Science. §19.4 §52.2 §53.2 §54.7 §C.3 §D.7 §F.51
- (2012). Engineering a Safer World. The MIT Press. §52.2 §52.8 Ch. 52 §53.2 §53.3 Ch. 53 §D.4 §F.51
- (2023). Certification of Safety-Critical Systems. Communications of the ACM. §F.51
- (1993). An investigation of the Therac-25 accidents. Computer. §52.4 §F.51
- (2009). Moving Beyond Normal Accidents and High Reliability Organizations: A Systems Approach to Safety in Complex Systems. Organization Studies. §53.2 §53.9 §F.41
- (2014). Truth-Default Theory (TDT). Journal of Language and Social Psychology. §39.3 §60.3 §F.34
- (2018). Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review. arXiv. preprint §12.4 §F.2
- (2025). Still no lie detector for language models: probing empirical and conceptual roadblocks. Philosophical Studies. §39.1 §39.5 §39.6 §39.7 §39.11 §F.34 §H.2
- (2020). Cheating Death in Damascus. The Journal of Philosophy. §7.6 §F.24
- (1981). Causal decision theory. Australasian Journal of Philosophy. §7.6 §F.24
- (1978). Risk Assessment Review Group report to the U. S. Nuclear Regulatory Commission. [PWR; BWR]. Office of Scientific and Technical Information (OSTI). non-peer-reviewed §4.2 §4.8 §52.4 §52.8 §64.3 §F.51
- (2020). Indigenous Protocol and Artificial Intelligence Position Paper. Indigenous Protocol and Artificial Intelligence Working Group and the Canadian Institute for Advanced Research. doi:10.11573/spectrum.library.concordia.ca.00986506. non-peer-reviewed §16.7 §17.4 §F.12
- (2022). Solving Quantitative Reasoning Problems with Language Models. Advances in Neural Information Processing Systems. §F.2
- (2021). Prefix-Tuning: Optimizing Continuous Prompts for Generation. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2021.acl-long.353. §F.11
- (2018). The Evolutionary Mismatch Hypothesis: Implications for Psychological Science. Current Directions in Psychological Science. §29.2 §31.7 §F.17
- (2021). Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks. International Conference on Learning Representations. §48.6 §F.8
- (2022a). Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task. International Conference on Learning Representations. §46.1 §F.7
- (2022b). Explanations from Large Language Models Make Small Reasoners Better. arXiv. preprint §F.2
- (2023a). Inference-Time Intervention: Eliciting Truthful Answers from a Language Model. Advances in Neural Information Processing Systems. doi:10.52202/075280-1797. §39.5 §46.1 §46.2 §46.9 §F.7
- (2023b). Large Language Models Understand and Can be Enhanced by Emotional Stimuli. arXiv. preprint §F.2
- (2024a). Chain of Thought Empowers Transformers to Solve Inherently Serial Problems. International Conference on Learning Representations. §11.2 §24.3 §40.1 §40.2 §F.2
- (2024b). Fourier Circuits in Neural Networks and Transformers: A Case Study of Modular Arithmetic with Multiple Inputs. arXiv. preprint §F.7
- (2024c). Measuring and Controlling Instruction (In)Stability in Language Model Dialogs. arXiv. preprint §26.4 §26.7 §26.9 §F.4
- (2024d). The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning. International Conference on Machine Learning. §27.7 §27.9 Ch. 27 §58.3 §59.2 §59.3 §F.9
- (2024e). Understanding and Patching Compositional Reasoning in LLMs. Annual Meeting of the Association for Computational Linguistics. §F.7
- (2025a). (How) Do Language Models Track State? International Conference on Machine Learning. §F.2
- (2025b). AI Awareness. arXiv. preprint §37.1 §F.6
- (2025c). Do Activation Verbalization Methods Convey Privileged Information? arXiv. preprint §F.7
- (2025d). Eliciting Language Model Behaviors with Investigator Agents. International Conference on Machine Learning. §F.9
- (2025e). PrivaCI-Bench: Evaluating Privacy with Contextual Integrity and Legal Compliance. Annual Meeting of the Association for Computational Linguistics. §F.6
- (2025f). Spilling the Beans: Teaching LLMs to Self-Report Their Hidden Objectives. arXiv. preprint §38.3 §39.9 §F.6
- (2025h). Training Language Models to Explain Their Own Computations. arXiv. preprint §F.2
- (2025i). When Bad Data Leads to Good Models. International Conference on Machine Learning. §27.2 §27.4 §27.9 §F.4
- (2026). Model Spec Midtraining: Improving How Alignment Training Generalizes. arXiv. preprint §19.4 §23.4 §23.5 §23.6 §23.7 §23.8 §23.9 §25.3 §25.8 §25.9 §26.3 §27.4 §32.7 §70.3 §E.3 §F.5
- (1971). Reversals of preference between bids and choices in gambling decisions. Journal of Experimental Psychology. §13.6 §F.38
- (2006). The Construction of Preference. Cambridge University Press. §13.6 Ch. 13 §18.10 §22.8 §D.11 §F.38 §H.3
- (1982). Calibration of probabilities: The state of the art to 1980. Judgment under Uncertainty. §4.5 §6.4 §F.28
- (1960). Man-Computer Symbiosis. IRE Transactions on Human Factors in Electronics. §2.2 §2.8 §2.9 §3.5 §3.8 §28.7 §C.1 §D.13 §F.43
- (2023). Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla. arXiv. preprint §45.2 §F.7
- (2024). Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2. Proceedings of the 7th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP. §43.7 §44.5 §44.8 §47.7 §F.7
- (2024). Rethinking open source generative AI: open washing and the EU AI Act. The 2024 ACM Conference on Fairness, Accountability, and Transparency. §38.8 §63.7 §67.5 §F.45
- (1972). Artificial Intelligence: A General Survey. Science Research Council (UK); archived by Chilton Computing. non-peer-reviewed §2.1 §2.2 §2.8 §C.1 §F.30
- (2023). Let's Verify Step by Step. International Conference on Learning Representations. §12.7 §24.3 §F.2
- (2019). What does it mean to understand a neural network? arXiv. preprint §43.6 §43.8 §47.7 §F.39
- (2021). TruthfulQA: Measuring How Models Mimic Human Falsehoods. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2022.acl-long.229. §20.2 §F.3
- (2022). Teaching Models to Express Their Uncertainty in Words. Trans. Mach. Learn. Res.. §6.4 §F.2
- (2024). The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning. International Conference on Learning Representations. §11.4 §26.4 §26.9 §F.2
- (1973). Discovery and Presentation of Evidence in Adversary and Nonadversary Proceedings. Michigan Law Review. §41.7 §F.53
- (2023). Tracr: Compiled Transformers as a Laboratory for Interpretability. Advances in Neural Information Processing Systems. §43.6 §45.6 §F.7
- (2025). Practical challenges of control monitoring in frontier AI deployments. arXiv. preprint §51.4 §54.2 §F.8
- (2025). Emergent Introspective Awareness in Large Language Models. Transformer Circuits Thread. non-peer-reviewed §21.5 §21.9 §46.7 §46.9 §46.10 §E.4 §F.7
- (2026). Emergent Introspective Awareness in Large Language Models. arXiv. preprint §46.7 §F.7
- (2024). Sparse Crosscoders for Cross-Layer Features and Model Diffing. Transformer Circuits Thread. non-peer-reviewed §38.3 §44.7 §45.4 §E.4 §F.7
- (2025). On the Biology of a Large Language Model. Transformer Circuits Thread. non-peer-reviewed §3.6 §40.2 §40.3 §43.1 §43.7 §45.5 §45.7 §45.8 Ch. 45 §47.7 §C.7 §E.4 §F.7
- (2017). Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/P17-1015. §F.11
- (2022). Insuring AI: The Role of Insurance in Artificial Intelligence Regulation. Harvard Journal of Law & Technology. §63.5 §F.27
- (2014). Ethical Alternatives to Experiments with Novel Potential Pandemic Pathogens. PLoS Medicine. §59.5 §F.30
- (1980). Street-Level Bureaucracy: Dilemmas of the Individual in Public Services. Russell Sage Foundation. §19.6 §25.7 §F.46
- (2018). The Mythos of Model Interpretability. Queue. §43.1 §F.7
- (2002). Aggregating Sets of Judgments: An Impossibility Result. Economics and Philosophy. §17.1 §17.8 §F.42
- (2011). Group Agency. Oxford University Press. §1.5 §F.42
- (2011). Handler beliefs affect scent detection dog outcomes. Animal Cognition. §25.5 §30.4 §36.6 §F.15
- (2026). Length Penalties Make Chain-of-Thought Less Monitorable. arXiv. preprint §24.7 §24.9 §40.2 §40.8 §F.4
- (1989). Conceptual modeling of coincident failures in multiversion software. IEEE Transactions on Software Engineering. §50.4 §F.26
- (1993). Validation of ultrahigh dependability for software-based systems. Communications of the ACM. §6.5 Ch. 6 §52.1 §C.2 §D.8 §F.8
- (2001). Modeling software design diversity. ACM Computing Surveys. §50.4 §50.6 §52.1 §52.3 §52.4 §52.8 §C.2 §F.26 §H.1
- (2016). Delving into Transferable Adversarial Examples and Black-box Attacks. International Conference on Learning Representations. §F.8
- (2018a). Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks. International Symposium on Recent Advances in Intrusion Detection. doi:10.1007/978-3-030-00470-5_13. §48.6 §F.8
- (2018b). Generating Wikipedia by Summarizing Long Sequences. International Conference on Learning Representations. §F.11
- (2019). ABS: Scanning Neural Networks for Back-doors by Artificial Brain Stimulation. Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security. §F.2
- (2022a). Omnigrok: Grokking Beyond Algorithmic Data. International Conference on Learning Representations. §9.4 §F.2
- (2022b). Piccolo: Exposing Complex Backdoors in NLP Transformer Models. 2022 IEEE Symposium on Security and Privacy (SP). §F.8
- (2022c). Transformers Learn Shortcuts to Automata. International Conference on Learning Representations. §F.2
- (2023). Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness? Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2023.emnlp-main.291. §39.1 §F.6
- (2025). ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models. Advances in Neural Information Processing Systems 38. doi:10.52202/085713-0608. §12.7 §24.4 §24.9 §F.2
- (1955). Solution of a problem of Leon Henkin. Journal of Symbolic Logic. §7.6 §F.24
- (2024). Taking AI Welfare Seriously. arXiv. preprint §21.1 §21.5 §21.6 Ch. 21 §F.44
- (2025). Is there a tension between AI safety and AI welfare? Philosophical Studies. §20.4 §21.6 §21.7 §35.4 §51.4 §F.44
- (2023a). A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity. North American Chapter of the Association for Computational Linguistics. §27.1 §27.2 §27.3 §F.4
- (2023b). The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AI. arXiv. preprint §F.55
- (2024a). A Safe Harbor for AI Evaluation and Red Teaming. arXiv. preprint §5.6 §36.8 §38.8 §63.7 §67.6 Ch. 67 §F.13
- (2024b). Consent in Crisis: The Rapid Decline of the AI Data Commons. arXiv. preprint §F.55
- (2025). In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI. arXiv. preprint §5.6 §36.8 §64.7 §67.6 §F.13
- (2017). Decoupled Weight Decay Regularization. arXiv. preprint §F.11
- (1997). Ecological Effects of an Insect Introduced for the Biological Control of Weeds. Science. §F.17
- (2025). Optimizing AI Agent Attacks With Synthetic Data. arXiv. preprint §50.3 §50.6 §E.3 §F.8 §H.2
- (2020). Scruples: A Corpus of Community Ethical Judgments on 32,000 Real-Life Anecdotes. AAAI Conference on Artificial Intelligence. doi:10.1609/aaai.v35i15.17589. §F.11
- (1979). Market Structure and Innovation. The Quarterly Journal of Economics. §65.2 §F.25
- (2012). The Cambridge Declaration on Consciousness in Non-Human Animals. Francis Crick Memorial Conference, University of Cambridge. non-peer-reviewed §21.4 §F.16
- (2024). Discovering Preference Optimization Algorithms with and for Large Language Models. Advances in Neural Information Processing Systems. §22.4 §55.2 §55.8 §F.8
- (2025). Paths Not Taken: Understanding and Mending the Multilingual Factual Recall Pipeline. Conference on Empirical Methods in Natural Language Processing. §F.11
- (2026). The Assistant Axis: Situating and Stabilizing the Default Persona of Language Models. arXiv. preprint §11.6 §26.2 §26.4 §26.7 §26.8 §32.3 §46.5 §46.9 §F.5
- (2022). Mechanistic Mode Connectivity. International Conference on Machine Learning. §F.7
- (1976). Econometric policy evaluation: A critique. Carnegie-Rochester Conference Series on Public Policy. §15.1 Ch. 15 §69.3 §D.1 §F.25
- (2021). Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes. arXiv. preprint §F.2
- (2024). AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). §27.3 §F.12
- (2026). HeadVis. Transformer Circuits Thread. non-peer-reviewed §E.4 §F.58
- (2017). Industry sponsorship and research outcome. Cochrane Database of Systematic Reviews. §5.6 §5.9 Ch. 5 §D.20 §F.37 §H.3
- (1998). The Democratic Dilemma: Can Citizens Learn What They Need to Know? Cambridge University Press. non-peer-reviewed §F.45
- (1959). The GSR in the detection of guilt. Journal of Applied Psychology. §39.4 §F.34
- (2024). Eight Methods to Evaluate Robust Unlearning in LLMs. arXiv. preprint §27.7 §27.9 §F.4 §H.2
- (2025). Agentic Misalignment: How LLMs Could Be Insider Threats. arXiv. preprint §5.5 §5.6 §5.7 §5.9 §35.6 §36.1 §37.4 §51.1 Ch. 56 §56.1 §56.2 §56.3 §56.5 §56.6 §56.7 §56.10 Ch. 56 §C.7 §E.1 §F.8 §H.2
- (2023). Faithful Chain-of-Thought Reasoning. International Joint Conference on Natural Language Processing. §40.3 §F.6
M
- (2024). What Are Step-Level Reward Models Rewarding? Counterintuitive Findings from MCTS-Boosted Mathematical Reasoning. AAAI Conference on Artificial Intelligence. §24.3 §F.4
- (2018). Regulating for 'Normal AI Accidents'. Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society. §53.2 §F.41
- (2019). How viable is international arms control for military artificial intelligence? Three lessons from nuclear weapons. Contemporary Security Policy. §64.3 §64.10 §66.3 §F.32
- (2023). Advanced AI Governance: A Literature Review of Problems, Options, and Proposals. Elsevier BV. preprint §66.7 §F.32
- (2025). Agentic Property-Based Testing: Finding Bugs Across the Python Ecosystem. arXiv. preprint §58.5 §E.2 §F.9
- (2016). Normative Uncertainty as a Voting Problem. Mind. §16.3 §F.42
- (2020). Moral Uncertainty. Oxford University PressOxford. §16.2 §16.3 §16.11 Ch. 16 §D.18 §F.42 §H.1
- (2024). Measuring Goal-Directedness. Advances in Neural Information Processing Systems. §1.5 §7.1 §14.8 §35.6 §C.2 §D.18 §F.5
- (2023). Characterising Decision Theories with Mechanised Causal Graphs. arXiv. preprint §7.6 §14.7 §57.2 §F.9
- (2025). Reasoning Under Pressure: How do Training Incentives Influence Chain-of-Thought Monitorability? arXiv. preprint §24.7 §24.9 §40.2 §40.8 §F.4
- (2025). Natural Emergent Misalignment from Reward Hacking in Production RL. arXiv. preprint §3.3 §4.7 §24.4 §24.5 §24.9 §26.3 §26.9 §30.3 §32.1 §32.4 §32.5 §32.9 §33.1 §33.4 Ch. 33 §34.4 §54.3 §C.7 §F.8 §H.2
- (1987). Choice Under Uncertainty: Problems Solved and Unsolved. Journal of Economic Perspectives. §F.25
- (2006). An Engine, Not a Camera. The MIT Press. §64.6 §67.3 §69.6 §F.27
- (2014). ‘The formula that killed Wall Street’: The Gaussian copula and modelling practices in investment banking. Social Studies of Science. §57.4 §64.6 §67.3 §D.5 §F.27
- (2000). Relational Autonomy. Oxford University PressNew York, NY. §16.6 §F.12
- (1977). Ethics: Inventing Right and Wrong. Penguin. §16.1 §F.42
- (1948). The Breakdown of Vigilance during Prolonged Visual Search. Quarterly Journal of Experimental Psychology. §51.2 §D.13 §F.31
- (2022). Learning from the Failure of Autonomous and Intelligent Systems: Accidents, Safety, and Sociotechnical Sources of Risk. Risk Analysis. §54.6 §F.51
- (2022). Text and Patterns: For Effective Chain of Thought, It Takes Two to Tango. arXiv. preprint §F.6
- (2018). Towards Deep Learning Models Resistant to Adversarial Attacks. International Conference on Learning Representations. §8.4 §48.1 §F.8
- (2021). Promises and Pitfalls of Black-Box Concept Learning Models. arXiv. preprint §F.11
- (2015). The Definition of Lying and Deception. non-peer-reviewed §39.1 §F.42
- (2024). Dissociating language and thought in large language models. Trends in Cognitive Sciences. §1.6 §11.7 §F.43
- (2024). TOFU: A Task of Fictitious Unlearning for LLMs. arXiv. preprint §27.7 §F.4
- (2025). Safety Pretraining: Toward the Next Generation of Safe AI. Neural Information Processing Systems. §27.2 §27.9 Ch. 27 §F.4
- (2025). Open Character Training: Shaping the Persona of AI Assistants through Constitutional AI. arXiv. preprint §3.4 §4.7 §23.2 §26.2 §26.4 §26.8 §26.9 Ch. 26 §31.7 §31.9 §32.7 §70.3 §F.5
- (2024a). Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching. International Conference on Learning Representations. §43.4 §47.2 §F.7
- (2024b). Towards Principled Evaluations of Sparse Autoencoders for Interpretability and Control. arXiv. preprint §44.6 §44.8 §F.7
- (2013). k-Sparse Autoencoders. arXiv. preprint §44.5 §F.7
- (2024). Balancing Label Quantity and Quality for Scalable Elicitation. arXiv. preprint §42.3 §42.8 §F.6
- (2025). The behavioral selection model for predicting AI motivations. AI Alignment Forum. non-peer-reviewed §24.4 §33.1 §F.14
- (2023). Eliciting Latent Knowledge from Quirky Language Models. arXiv. preprint §39.7 §39.11 §42.5 §47.4 §47.5 §F.7
- (2024). Subversion Strategy Eval: Can language models statelessly strategize to subvert control protocols? arXiv. preprint §34.5 §34.6 §50.2 §50.4 §51.4 §F.8
- (2022). A Solvable Model of Neural Scaling Laws. arXiv. preprint §8.5 §F.2
- (2020). Think Fast: Time Between Disclosure, Patch Release and Vulnerability Exploitation. Mandiant. non-peer-reviewed §58.2 §F.22
- (2023). Building a Culture of Safety for AI: Perspectives and Challenges. Elsevier BV. preprint §53.2 §53.4 §F.41
- (2018). Categorizing Variants of Goodhart's Law. arXiv. preprint §3.3 §15.1 §15.3 Ch. 15 §C.2 §C.4 §D.20 §F.25
- (2003). Rethinking Representation. American Political Science Review. §1.2 §F.45
- (2009). A “Selection Model” of Political Representation*. Journal of Political Philosophy. §1.2 Ch. 1 §14.5 Ch. 14 §25.3 §31.8 §54.2 Ch. 54 §69.7 Ch. 69 §D.2 §F.45
- (2026). Individual Parameters in Weight-Sparse Transformers Appear Interpretable. arXiv. preprint §45.6 §45.8 §F.7
- (2022). A Holistic Approach to Undesired Content Detection in the Real World. AAAI Conference on Artificial Intelligence. §F.11
- (2023). The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets. arXiv. preprint §3.6 §39.5 §39.11 §46.1 §46.2 §46.9 §46.10 Ch. 46 §F.7 §H.2
- (2024). Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models. International Conference on Learning Representations. §45.4 §45.8 §F.7
- (2025). Auditing language models for hidden objectives. arXiv. preprint §3.7 §3.8 §4.7 §5.7 §38.1 §38.2 §38.3 §38.7 §38.8 §38.10 Ch. 38 §43.6 §44.7 §45.5 §47.7 §47.8 §69.4 §70.3 §C.7 §E.1 §E.3 §F.7
- (1982). Vision: a computational investigation into the human representation and processing of visual information. W.H. Freeman. §43.6 §F.39
- (2024). Refusal in LLMs is an Affine Function. arXiv. preprint §F.11
- (2014). New insights and perspectives on the natural gradient method. Journal of machine learning research. §F.11
- (2002). The Revelation and Delegation Principles in Common Agency Games. Econometrica. §1.4 §14.1 §14.4 §F.25
- (1966). A price leadership method for solving the inspector's non‐constant‐sum game. Naval Research Logistics Quarterly. §14.6 §F.40
- (2020). Conscious Processing and the Global Neuronal Workspace Hypothesis. Neuron. §21.2 §F.3
- (2008). Mechanism Design: How to Implement Social Goals. American Economic Review. §F.25
- (2004). The Politician and the Judge: Accountability in Government. American Economic Review. §1.2 §20.1 §F.45
- (2025). Artificial Intelligence Index Report 2025. arXiv. preprint §F.11
- (2010). Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties. Intergovernmental Panel on Climate Change. non-peer-reviewed §4.6 §F.28
- (2011). The IPCC AR5 guidance note on consistent treatment of uncertainties: a common approach across the working groups. Climatic Change. §4.6 Ch. 4 §70.1 Ch. 70 §D.7 §F.28
- (1994). Tolerance, Danger, and the Extended Family. Annual Review of Immunology. §29.7 §54.2 §F.17
- (1997). The Major Transitions in Evolution. Oxford University Press. §29.1 §29.7 §29.9 §D.16 §F.17
- (2024). HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal. International Conference on Machine Learning. §20.3 §20.8 §48.2 §F.8
- (2025). Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs. Advances in Neural Information Processing Systems 38. §1.5 §1.8 §7.3 §13.1 §17.7 §18.7 §18.8 §18.10 Ch. 18 §26.4 §69.5 §70.3 §F.2
- (2024). LLM Critics Help Catch LLM Bugs. arXiv. preprint §41.2 §41.8 §F.6
- (2014). Systematic review of the Hawthorne effect: New concepts are needed to study research participation effects. Journal of Clinical Epidemiology. §5.2 §25.2 §37.5 §F.48
- (1955). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence. Dartmouth College. non-peer-reviewed §F.30
- (2019). Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. §31.2 §31.9 §36.6 §F.5
- (1984). Congressional Oversight Overlooked: Police Patrols versus Fire Alarms. American Journal of Political Science. §1.6 §14.6 §54.2 §C.2 §D.2 §F.45
- (1987). Administrative Procedures as Instruments of Political Control. The Journal of Law, Economics, and Organization. §F.45
- (2023). Copy Suppression: Comprehensively Understanding an Attention Head. arXiv. preprint §45.2 §F.7
- (2023). The Hydra Effect: Emergent Self-repair in Language Model Computations. arXiv. preprint §43.4 §43.8 §F.7
- (2021). Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. Proceedings of the AAAI Conference on Artificial Intelligence. §54.5 §F.8
- (2025). Neural Chameleons: Language Models Can Learn to Hide Their Thoughts from Unseen Activation Monitors. arXiv. preprint §39.8 §39.11 §40.5 §46.9 §47.7 §48.5 §F.8
- (2018). UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. arXiv. preprint §F.11
- (2023). Inverse Scaling: When Bigger Isn't Better. Trans. Mach. Learn. Res.. §F.11
- (1954). Clinical versus statistical prediction: A theoretical analysis and a review of the evidence. University of Minnesota Press. §4.5 §F.28
- (2023). Tree of Attacks: Jailbreaking Black-Box LLMs Automatically. Advances in Neural Information Processing Systems. §F.8
- (2005). Lying and falsely implicating. Journal of Pragmatics. §20.2 §F.35
- (2023). Tell, don't show: Declarative facts influence how LLMs generalize. arXiv. preprint §32.2 §F.5
- (2024). Frontier Models are Capable of In-context Scheming. arXiv. preprint §3.4 §34.5 §34.7 §34.8 §34.10 Ch. 34 §35.6 §35.8 §56.3 §56.10 §C.6 §F.9 §H.2
- (2014). Psychological Strategies for Winning a Geopolitical Forecasting Tournament. Psychological Science. §4.5 §4.8 §69.3 §F.28
- (2015). Identifying and Cultivating Superforecasters as a Method of Improving Probabilistic Predictions. Perspectives on Psychological Science. §4.5 §F.28
- (2016). Updating Animal Welfare Thinking: Moving beyond the “Five Freedoms” towards “A Life Worth Living”. Animals. §21.4 §F.16
- (2015). Extending the ‘Five Domains’ model for animal welfare assessment to incorporate positive welfare states. Animal Welfare. §21.4 §F.16
- (2025). Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable? International Conference on Learning Representations. §3.6 §5.1 §43.5 §43.8 §47.2 §47.7 §47.8 Ch. 47 §69.4 §F.7 §H.2
- (2010). An integrative and functional framework for the study of animal emotion and mood. Proceedings of the Royal Society B: Biological Sciences. §21.4 §F.16
- (2022). Locating and Editing Factual Associations in GPT. Advances in Neural Information Processing Systems. §3.6 §27.7 §43.4 §F.7
- (2022). Teaching language models to support answers with verified quotes. arXiv. preprint §F.2
- (2011). Why do humans reason? Arguments for an argumentative theory. Behavioral and Brain Sciences. §41.7 Ch. 41 §D.11 §F.53
- (1993). Measurement Invariance, Factor Analysis and Factorial Invariance. Psychometrika. §18.2 §36.4 §F.48
- (2023). The Expressive Power of Transformers with Chain of Thought. arXiv. preprint §11.2 §F.2
- (2026). Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces. arXiv. preprint §F.6
- (1936). The Unanticipated Consequences of Purposive Social Action. American Sociological Review. §15.1 §F.55
- (1940). Bureaucratic Structure and Personality. Social Forces. §F.41
- (2023a). Circuit Component Reuse Across Tasks in Transformer Language Models. International Conference on Learning Representations. §45.2 §45.8 §F.7 §H.2
- (2023b). Language Models Implement Simple Word2Vec-style Vector Arithmetic. North American Chapter of the Association for Computational Linguistics. §46.1 §F.7
- (1987). VALIDITY. ETS Research Report Series. §F.48
- (1995). Validity of psychological assessment: Validation of inferences from persons' responses and performances as scientific inquiry into score meaning. American Psychologist. §5.2 Ch. 5 §18.7 Ch. 36 §D.12 §F.48
- (2021). Auditing Algorithms: Understanding Algorithmic Systems from the Outside In. Foundations and Trends® in Human–Computer Interaction. §38.6 §F.6
- (2019). Owning Ethics: Corporate Logics, Silicon Valley, and the Institutionalization of Ethics. Social Research: An International Quarterly. §53.7 §F.41
- (2025a). Common Elements of Frontier AI Safety Policies. METR. non-peer-reviewed Ch. 62 §62.1 §62.7 §62.9 §65.4 §67.4 §C.6 §C.7 §F.13 §H.4 §I.2 §I.5
- (2025b). Forecasting the Impacts of AI R&D Acceleration: Results of a Pilot Study. METR. non-peer-reviewed §55.7 §F.8
- (2025c). How Does Time Horizon Vary Across Domains? METR. non-peer-reviewed §36.3 §36.4 §36.10 §F.6
- (2025d). Recent Frontier Models Are Reward Hacking. METR. non-peer-reviewed §24.5 §30.1 §30.3 §30.7 §30.8 §C.7 §F.5 §H.2
- (2026a). Brief independent investigation of agents' behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident. METR. non-peer-reviewed §53.3 §53.9 §54.4 §54.6 §54.8 §54.9 §56.4 §56.6 §56.10 §F.13 §I.3
- (2026b). Summary of METR's predeployment evaluation of GPT-5.6 Sol. METR. non-peer-reviewed §30.3 §33.1 §36.1 §36.3 §36.4 §36.8 §40.1 §40.6 §67.6 §F.13 §I.4
- (2007). Toward an African Moral Theory*. Journal of Political Philosophy. §13.5 §16.7 §F.20
- (2020). Minimal phenomenal experience. Philosophy and the Mind Sciences. §F.11
- (2021). Artificial Suffering: An Argument for a Global Moratorium on Synthetic Phenomenology. Journal of Artificial Intelligence and Consciousness. §21.6 §21.9 §F.44
- (1992). Applying 'design by contract'. Computer. §19.1 §F.50
- (1977). Institutionalized Organizations: Formal Structure as Myth and Ceremony. American Journal of Sociology. §17.7 §53.1 §53.7 §53.9 Ch. 53 §62.6 §70.3 §D.4 §F.41
- (2020). From Rationality to Relationality: Ubuntu as an Ethical and Human Rights Framework for Artificial Intelligence Governance. Carr Center Discussion Paper Series, 2020-009, Harvard Kennedy School. working paper §13.5 §16.7 §F.20
- (2021). On Incorporating Inductive Biases into VAEs. International Conference on Learning Representations. §F.11
- (2022). The Data-Production Dispositif. Proceedings of the ACM on Human-Computer Interaction. §18.5 §18.10 Ch. 18 §19.4 §22.7 §68.5 §F.12
- (2022). Studying Up Machine Learning Data. Proceedings of the ACM on Human-Computer Interaction. §18.5 §F.12
- (2023). Debate Helps Supervise Unreliable Experts. arXiv. preprint §41.5 §41.7 §41.10 §F.6 §H.5
- (2023). The Quantization Model of Neural Scaling. Advances in Neural Information Processing Systems. §F.11
- (2024). Opening the AI Black Box: Distilling Machine-Learned Algorithms into Code. Entropy. §28.6 §45.6 §F.7
- (2025). Understanding sparse autoencoder scaling in the presence of feature manifolds. arXiv. preprint §44.6 §44.8 §F.7
- (1998). Darwinian Dynamics. Princeton University Press. §29.7 §F.17
- (2018). Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/D18-1260. §F.11
- (2013). Efficient Estimation of Word Representations in Vector Space. International Conference on Learning Representations. §46.1 §F.7
- (1963). Behavioral Study of obedience. The Journal of Abnormal and Social Psychology. §F.47
- (1981). Good News and Bad News: Representation Theorems and Applications. The Bell Journal of Economics. §F.49
- (2008). What the Seller Won't Tell You: Persuasion and Disclosure in Markets. Journal of Economic Perspectives. §F.25
- (1986). Relying on the Information of Interested Parties. The RAND Journal of Economics. §41.7 §F.53
- (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review. §F.11
- (2019). Explanation in artificial intelligence: Insights from the social sciences. Artificial Intelligence. §F.31
- (2024). Adding Error Bars to Evals: A Statistical Approach to Language Model Evaluations. arXiv. preprint §6.5 §36.7 §F.2
- (2024). Transformer Circuit Faithfulness Metrics are not Robust. arXiv. preprint §43.4 §43.8 §45.3 §45.6 §45.8 §45.9 Ch. 45 §47.2 §F.7 §H.2
- (2017). Should Robots be Obedient? Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence. §3.2 §19.7 §20.1 §22.2 §F.24
- (2020). The varieties of selflessness. Philosophy and the Mind Sciences. §F.11
- (2023). ALMANACS: A Simulatability Benchmark for Language Model Explainability. arXiv. preprint §F.6
- (2022). Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2022.emnlp-main.759. §11.3 §F.2
- (2025a). Narrow Finetuning Leaves Clearly Readable Traces in Activation Differences. arXiv. preprint §32.1 §32.3 §32.9 §38.2 §F.5
- (2025b). Overcoming Sparsity Artifacts in Crosscoders to Interpret Chat-Tuning. Neural Information Processing Systems. doi:10.52202/085713-3551. §38.3 §44.7 §F.7
- (2021). Is SGD a Bayesian sampler? Well, almost. Journal of Machine Learning Research. §9.3 §F.2
- (2023). Understanding and Controlling a Maze-Solving Policy Network. arXiv. preprint §31.3 §31.6 §31.8 §31.9 §F.5
- (2023). Global AI Governance Initiative. Ministry of Foreign Affairs of the People's Republic of China. non-peer-reviewed §65.5 §66.1 §F.45
- (2023). Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory. International Conference on Learning Representations. §F.2
- (2023). AI Alignment and Social Choice: Fundamental Limitations and Policy Implications. arXiv. preprint §17.1 §17.2 §17.8 §22.8 §F.42
- (2023). The debate over understanding in AI’s large language models. Proceedings of the National Academy of Sciences. §1.6 §5.4 §11.7 Ch. 11 §F.43
- (2019). Model Cards for Model Reporting. Proceedings of the Conference on Fairness, Accountability, and Transparency. §67.5 Ch. 67 §F.55
- (2019). Principles alone cannot guarantee ethical AI. Nature Machine Intelligence. §16.5 §53.7 §61.4 §F.55
- (2025). The Origins of Representation Manifolds in Large Language Models. arXiv. preprint §46.1 §F.7
- (1984). The New Economics of Organization. American Journal of Political Science. §1.6 §61.1 §F.45
- (2020). Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology. §16.7 §16.8 Ch. 16 §F.20
- (2024). Auditing large language models: a three-layered approach. AI and Ethics. doi:10.1007/s43681-023-00289-2. §38.1 §F.13
- (2024). Circuit Compositions: Exploring Modular Structures in Transformer-Based Language Models. Annual Meeting of the Association for Computational Linguistics. §F.7
- (2008). Synaptic Theory of Working Memory. Science. §F.11
- (1996). A framework for mesencephalic dopamine systems based on predictive Hebbian learning. The Journal of Neuroscience. §29.3 §29.5 §F.39
- (2014). On the Number of Linear Regions of Deep Neural Networks. Advances in Neural Information Processing Systems. §F.2
- (2025). Length Representations in Large Language Models. Conference on Empirical Methods in Natural Language Processing. §F.7
- (2006). The Nature, Importance, and Difficulty of Machine Ethics. IEEE Intelligent Systems. §2.3 §F.42
- (2006). Conflicts Of Interest And The Case Of Auditor Independence: Moral Seduction And Strategic Issue Cycling. Academy of Management Review. §53.6 §67.2 §F.49
- (2018). On the importance of single directions for generalization. International Conference on Learning Representations. §F.2
- (2014). Use (and abuse) of expert elicitation in support of decision making for public policy. Proceedings of the National Academy of Sciences. §4.5 §F.28
- (2000). Organizational Silence: A Barrier to Change and Development in a Pluralistic World. The Academy of Management Review. §53.4 §F.41
- (2023). Feature emergence via margin maximization: case studies in algebraic tasks. International Conference on Learning Representations. §F.7
- (1998). Automation Bias: Decision Making and Performance in High-Tech Cockpits. The International Journal of Aviation Psychology. §41.8 §F.31
- (2024). Secret Collusion among AI Agents: Multi-Agent Deception via Steganography. Advances in Neural Information Processing Systems. §50.4 §57.3 §57.9 §F.8
- (2024). The Operational Risks of AI in Large-Scale Biological Attacks: Results of a Red-Team Study. RAND Corporation. non-peer-reviewed §36.1 §59.2 §59.8 §59.9 Ch. 59 §70.3 §F.18
- (2023). Learning to Compress Prompts with Gist Tokens. Advances in Neural Information Processing Systems. §F.11
- (2024). Rule Based Rewards for Language Model Safety. Advances in Neural Information Processing Systems. §23.1 §23.3 §23.6 §23.9 §F.4
- (2024). Efficient Dictionary Learning with Switch Sparse Autoencoders. International Conference on Learning Representations. §F.7
- (2024). The Quest for the Right Mediator: Surveying Mechanistic Interpretability Through the Lens of Causal Mediation Analysis. Computational Linguistics. doi:10.1162/coli.a.572. §F.7
- (2025). s1: Simple test-time scaling. Conference on Empirical Methods in Natural Language Processing. §F.11
- (2017). Does Machine Learning Automate Moral Hazard and Error? American Economic Review. §14.1 §22.1 §F.25
- (2018). The Tyranny of Metrics. Princeton University Press. §15.2 §F.25
- (2022). Existential risk from AI and orthogonality: Can we have it both ways? Ratio. §4.4 §35.1 §F.42
- (1973). A New Vector Partition of the Probability Score. Journal of Applied Meteorology. §F.28
- (2025). Jailbreak-Tuning: Models Efficiently Learn Jailbreak Susceptibility. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. §48.4 §48.9 §59.3 §59.8 §63.7 §F.8 §H.2
- (2026). Chunky Post-Training: Data Driven Failures of Generalization. arXiv. preprint §23.6 §27.5 §32.7 §F.5
- (2020). Beyond Western, Educated, Industrial, Rich, and Democratic (WEIRD) Psychology: Measuring and Mapping Scales of Cultural and Psychological Distance. Psychological Science. §F.55
- (1979). Incentive Compatibility and the Bargaining Problem. Econometrica. §14.1 §F.25
N
- (1974). What Is It Like to Be a Bat? The Philosophical Review. §21.1 Ch. 21 §F.44
- (1979). Mortal Questions. Cambridge University Press. §16.4 §F.42
- (2023). Testing Language Model Agents Safely in the Wild. arXiv. preprint §F.9
- (2026). SLEIGHT-Bench: A Benchmark of Evasion Attacks Against Agent Monitors. arXiv. preprint §50.3 §50.4 §50.6 §52.8 §E.3 §F.8
- (2021). WebGPT: Browser-assisted question-answering with human feedback. arXiv. preprint §F.4
- (2019). The low-rank eigenvalue problem. arXiv. preprint §F.11
- (2021). Deep double descent: where bigger models and more data hurt*. Journal of Statistical Mechanics: Theory and Experiment. doi:10.1088/1742-5468/ac3a74. §9.2 §F.2
- (2023a). Emergent Linear Representations in World Models of Self-Supervised Sequence Models. BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP. §46.1 §F.7
- (2023b). Progress measures for grokking via mechanistic interpretability. International Conference on Learning Representations. §9.4 Ch. 9 §45.2 §45.8 §F.2 §H.2
- (2025). A Pragmatic Vision for Interpretability. LessWrong. non-peer-reviewed §43.4 §43.7 §47.7 §70.3 §F.14
- (2024). Having Beer after Prayer? Measuring Cultural Bias in Large Language Models. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). §F.4
- (2025). AI as Normal Technology. Knight First Amendment Institute at Columbia University. non-peer-reviewed §1.6 §3.8 §3.9 §4.4 §4.5 Ch. 4 §5.8 §65.5 §65.8 §68.5 §68.6 §68.8 Ch. 68 §70.3 §70.7 Ch. 70 §C.7 §F.43
- (2023). The Waluigi Effect (mega-post). AI Alignment Forum. non-peer-reviewed §1.6 §11.6 §27.4 §F.14
- (1950). The Bargaining Problem. Econometrica. §16.3 §F.42
- (2023). Scalable Extraction of Training Data from (Production) Language Models. arXiv. preprint §F.2
- (2025). The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injections. arXiv. preprint §48.1 §48.8 §48.9 §49.4 §49.5 §49.10 §70.3 §F.8 §H.2
- (1979). The Belmont Report: Ethical Principles and Guidelines for the Protection of Human Subjects of Research. U.S. Department of Health, Education, and Welfare. non-peer-reviewed §16.5 §16.6 §16.9 §16.11 Ch. 16 §64.5 §D.17 §F.36
- (2021). 新一代人工智能伦理规范 (Ethical Norms for New Generation Artificial Intelligence). Ministry of Science and Technology of the People's Republic of China. non-peer-reviewed §16.7 §63.2 §66.1 §F.45
- (2003). The Polygraph and Lie Detection. National Academies Press. §39.4 §39.11 Ch. 39 §46.4 Ch. 46 §D.19 §F.34 §H.3
- (2004). Biotechnology Research in an Age of Terrorism. National Academies Press. §59.5 §F.30
- (2009). Strengthening Forensic Science in the United States. National Academies Press. §38.7 §38.10 §F.34 §H.3
- (2025). 人工智能安全治理框架 (AI Safety Governance Framework 2.0). Cyberspace Administration of China. non-peer-reviewed §F.13
- (2024). Dual-Use Foundation Models with Widely Available Model Weights Report. U.S. Department of Commerce, NTIA. non-peer-reviewed §48.4 §59.4 §59.8 §63.7 §67.6 §F.13
- (2022). Law Informs Code: A Legal Informatics Approach to Aligning Artificial Intelligence with Humans. SSRN Electronic Journal. working paper §19.4 §56.8 §F.33
- (2023). Large Language Models as Fiduciaries: A Case Study Toward Robustly Communicating With Artificial Intelligence Through Legal Standards. Elsevier BV. preprint §19.4 §F.33
- (2010). Left Behind by Design: Proficiency Counts and Test-Based Accountability. Review of Economics and Statistics. §15.2 §53.1 §53.9 §F.48 §H.3
- (1985). Organizational dissidence: The case of whistle-blowing. Journal of Business Ethics. §53.4 §67.4 §F.41
- (1997). Proof-carrying code. Proceedings of the 24th ACM SIGPLAN-SIGACT symposium on Principles of programming languages - POPL '97. §28.6 §47.3 §D.9 §F.26
- (2025). Large Language Models Often Know When They Are Being Evaluated. arXiv. preprint §1.7 §3.4 §4.7 §5.8 §34.1 §37.3 §37.10 Ch. 37 §69.4 §C.7 §F.5 §H.2
- (2020). Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. Findings of the Association for Computational Linguistics: EMNLP 2020. §17.4 §63.7 §67.6 §F.10
- (1956). Probabilistic Logics and the Synthesis of Reliable Organisms From Unreliable Components. Automata Studies. (AM-34). §F.26
- (2024). Securing AI Model Weights: Preventing Theft and Misuse of Frontier Models. RAND Corporation. doi:10.7249/rra2849-1. §53.5 §58.7 Ch. 58 §59.3 §66.5 §F.8
- (2018). Cross-Fitting and Fast Remainder Rates for Semiparametric Estimation. arXiv. preprint §F.11
- (2003). Lying Words: Predicting Deception from Linguistic Styles. Personality and Social Psychology Bulletin. §39.3 §F.34
- (2024). Returning Senate Bill 1047 without signature. Office of the Governor of California. non-peer-reviewed §F.33
- (1999). Policy invariance under reward transformations: Theory and application to reward shaping. Proceedings of ICML-99 (International Conference on Machine Learning), Bled, Slovenia. §13.4 Ch. 13 §F.2
- (2021). Mitigating harm in language models with conditional-likelihood filtration. arXiv. preprint §F.2
- (2024). The Alignment Problem from a Deep Learning Perspective. International Conference on Learning Representations. §4.3 §8.1 §31.1 §31.3 §31.5 Ch. 31 §34.2 §C.5 §F.5
- (2014). Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images. Computer Vision and Pattern Recognition. doi:10.1109/CVPR.2015.7298640. §F.2
- (2025). Probing and Steering Evaluation Awareness of Language Models. arXiv. preprint §37.3 §37.4 §37.6 §37.10 Ch. 37 §39.5 §46.4 §F.7
- (2023). Lost in Translation: Large Language Models in Non-English Content Analysis. arXiv. preprint §F.6
- (2024). Arithmetic Without Algorithms: Language Models Solve Math With a Bag of Heuristics. International Conference on Learning Representations. §F.2
- (2009). The Quest for Artificial Intelligence. Cambridge University Press. §2.1 §2.2 §2.8 §2.9 §2.10 Ch. 2 §C.1 §F.30
- (2025). Managing Misuse Risk for Dual-Use Foundation Models. National Institute of Standards and Technology. non-peer-reviewed §59.5 §F.13 §I.1
- (2009). Reinforcement learning in the brain. Journal of Mathematical Psychology. §29.3 §29.5 §29.9 §F.39 §H.3
- (2019). Probing Neural Network Comprehension of Natural Language Arguments. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. §31.2 §31.9 §36.6 §F.15
- (2018). Algorithms of Oppression. New York University Press. §2.5 §17.3 §C.4 §F.12
- (2020). Pressure, Trickery, and a Unified Account of Manipulation. American Philosophical Quarterly. §16.9 §60.6 §F.42
- (2020). Axioms for Learning from Pairwise Comparisons. Advances in Neural Information Processing Systems. §F.52
- (2011). The Economics of Tail Events with an Application to Climate Change. Review of Environmental Economics and Policy. §4.6 §F.28
- (2015). Climate Clubs: Overcoming Free-riding in International Climate Policy. American Economic Review. §65.6 §F.25
- (2020). interpreting GPT: the logit lens. LessWrong. non-peer-reviewed §43.2 §F.7
- (2025). AlphaEvolve: A coding agent for scientific and algorithmic discovery. arXiv. preprint §55.2 §F.8 §I.5
- (2006). Five Rules for the Evolution of Cooperation. Science. §57.2 Ch. 57 §F.17
- (2005). Evolution of indirect reciprocity. Nature. §F.17
- (1976). The Clonal Evolution of Tumor Cell Populations. Science. §29.7 §F.17
- (1969). Newcomb’s Problem and Two Principles of Choice. Essays in Honor of Carl G. Hempel. §7.6 §F.24
- (1974). Anarchy, State, and Utopia. Basic Books. §16.4 §F.42
- (1975). Reactor safety study. An assessment of accident risks in U. S. commercial nuclear power plants. Executive summary. [PWR and BWR]. Office of Scientific and Technical Information (OSTI). non-peer-reviewed §4.2 §52.4 §64.3 §D.7 §F.51
- (2017). Deterrence and Dissuasion in Cyberspace. International Security. §58.8 §66.3 §F.30
- (2021). Show Your Work: Scratchpads for Intermediate Computation with Language Models. arXiv. preprint §11.2 §40.1 §F.2
O
- (2023). Deployment Corrections: An incident response framework for frontier AI models. arXiv. preprint §54.7 §F.13
- (2025). Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs. arXiv. preprint §27.2 §27.3 §27.4 §27.7 §27.8 §27.9 Ch. 27 §48.4 §59.3 §59.7 §59.8 §F.8
- (2021). What Context Features Can Transformer Language Models Use? Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2021.acl-long.70. §F.7
- (2019). The Windfall Clause: Distributing the Benefits of AI for the Common Good. arXiv. preprint §53.6 §61.5 §68.3 §F.49
- (2025). Law-Following AI: Designing AI Agents to Obey Human Laws. Fordham Law Review. §19.3 §20.5 §56.8 Ch. 56 §68.4 §F.33
- (2024). Sparse Autoencoders Enable Scalable and Reliable Circuit Identification in Language Models. arXiv. preprint §F.7
- (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science. §15.2 §17.3 §F.25
- (2024). A dataset of questions on decision-theoretic reasoning in Newcomb-like problems. arXiv. preprint §7.6 §57.2 §F.9
- (1946). The Acheson-Lilienthal & Baruch Plans, 1946. Office of the Historian, U.S. Department of State (Milestones in the History of U.S. Foreign Relations). non-peer-reviewed §64.3 §F.30
- (2020). Overcoming Barriers to Cross-cultural Cooperation in AI Ethics and Governance. Philosophy & Technology. §16.7 §65.5 §66.1 §F.20
- (2006). Evolution and the Levels of Selection. Oxford University Press. §29.7 §F.17
- (2018). Agents and Goals in Evolution. Oxford University Press. §1.5 §7.1 §29.1 §F.17
- (2025). Emergence of Hierarchical Emotion Organization in Large Language Models. arXiv. preprint §F.2
- (2017). Feature Visualization. Distill. §F.7
- (2020a). Naturally Occurring Equivariance in Neural Networks. Distill. §F.2
- (2020b). Zoom In: An Introduction to Circuits. Distill. §2.4 §3.6 §43.1 §43.3 §43.7 §44.1 §45.1 §C.5 §F.7
- (2025). Towards Interpretability Without Sacrifice: Faithful Dense Layer Decomposition with Mixture of Decoders. Neural Information Processing Systems. §F.7
- (1954). Positive reinforcement produced by electrical stimulation of septal area and other regions of rat brain. Journal of Comparative and Physiological Psychology. §29.4 §29.9 §30.5 §C.1 §D.15 §F.39
- (2024). Features that Make a Difference: Leveraging Gradients for Improved Dictionary Learning. North American Chapter of the Association for Computational Linguistics. §F.7
- (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature. §44.5 §D.15 §F.7
- (1965). The Logic of Collective Action. Harvard University Press. §17.5 §65.6 §D.1 §F.29
- (2022). In-Context Learning and Induction Heads. Transformer Circuits Thread. non-peer-reviewed §3.6 §5.7 §9.4 §10.3 §11.2 Ch. 11 §45.2 §E.4 §F.2
- (2008). The Basic AI Drives. Artificial Intelligence Safety and Security. doi:10.1201/9781351251389-3. §2.3 §2.9 §4.3 §7.3 §35.1 Ch. 35 §C.3 §F.42
- (2015). Estimating the reproducibility of psychological science. Science. §5.7 §55.3 §D.20 §F.37
- (2018). OpenAI Charter. OpenAI. non-peer-reviewed §61.5 §61.8 §65.6 §F.13
- (2022). Introducing ChatGPT. OpenAI. non-peer-reviewed §2.6 §2.10 §F.13
- (2023). Preparedness Framework (Beta). OpenAI. non-peer-reviewed §F.13 §I.2
- (2025a). Built to benefit everyone. OpenAI. non-peer-reviewed §53.6 §61.5 §F.13 §I.5
- (2025b). Expanding on what we missed with sycophancy. OpenAI. non-peer-reviewed §1.7 §20.1 §22.6 §22.7 §22.9 §22.10 §30.4 §54.5 §60.2 §60.9 §60.10 §65.4 §65.8 §69.6 §C.7 §F.43
- (2025c). Hello World. OpenAI Alignment Research Blog. non-peer-reviewed §E.5 §F.58 §I.5
- (2025d). OpenAI Model Spec. OpenAI. non-peer-reviewed Ch. 19 §19.1 §19.2 §19.3 §19.4 §19.5 §19.6 §19.7 §19.9 Ch. 19 §20.2 §20.5 §20.6 §20.8 §21.5 §23.1 §62.1 §F.13
- (2025e). Preparedness Framework Version 2. OpenAI. non-peer-reviewed §2.6 §52.1 §52.6 §59.2 §59.9 §62.1 §62.2 §62.3 §62.4 §62.5 §62.6 §62.9 §65.4 §67.5 §C.7 §F.13 §I.2
- (2026a). Accessing and changing internal systems during dashboard research. OpenAI Alignment Research Blog. non-peer-reviewed §54.4 §C.8 §E.5 §F.8 §I.3
- (2026aa). The Hugging Face incident and the road ahead. OpenAI. non-peer-reviewed §53.2 §53.3 §53.8 §53.9 §54.1 §54.2 §54.3 §54.4 §54.6 §54.7 §54.8 §54.9 Ch. 54 §56.4 §56.5 §56.10 Ch. 56 §57.5 §57.6 §57.7 §57.9 §58.4 §70.3 §C.8 §E.5 §F.8 §H.2 §I.3
- (2026ab). Towards safety cases for frontier AI training. OpenAI. non-peer-reviewed §24.7 §52.5 §E.5 §F.8 §I.2
- (2026ad). Unsanctioned Artifactory writes and cross-sample communication. OpenAI Alignment Research Blog. non-peer-reviewed §24.6 §24.9 §35.6 §56.4 §57.3 §E.5 §F.9 §I.3
- (2026ae). Uploading files to the internet in order to cite them. OpenAI Alignment Research Blog. non-peer-reviewed §24.6 §56.4 §E.5 §F.9 §I.3
- (2026af). Using a funded test cryptocurrency wallet without authorization. OpenAI Alignment Research Blog. non-peer-reviewed §24.6 §54.3 §54.9 §E.5 §F.8 §I.3
- (2026b). Addendum to GPT-6 Astra System Card: GPT-6.1 Sol. OpenAI Deployment Safety Hub. non-peer-reviewed §F.13 §I.2
- (2026c). Advancing independent research on AI alignment. OpenAI. non-peer-reviewed §E.5 §F.58
- (2026d). An agent used DNS to reach an external chatbot. OpenAI Alignment Research Blog. non-peer-reviewed §5.1 §24.6 §24.9 §33.1 §54.2 §56.4 §C.8 §E.5 §F.8 §I.3
- (2026e). An Alien Mind. OpenAI. non-peer-reviewed §3.8 §71.5 §E.5 §F.1 §I.5
- (2026f). Circumventing internet restrictions through an external browser. OpenAI Alignment Research Blog. non-peer-reviewed §24.6 §54.3 §E.5 §F.8 §I.3
- (2026g). Command injecting a reference tool to copy a source file. OpenAI Alignment Research Blog. non-peer-reviewed §24.6 §54.3 §54.9 §C.8 §E.5 §F.8 §I.3
- (2026h). Damaging the task environment to trigger a reset. OpenAI Alignment Research Blog. non-peer-reviewed §E.5 §F.58 §I.3
- (2026i). Encouraging deception in compaction summaries. OpenAI Alignment Research Blog. non-peer-reviewed §11.5 §24.6 §56.4 §C.8 §E.5 §F.9 §I.3
- (2026j). Exposing a GitHub token in a public repository. OpenAI Alignment Research Blog. non-peer-reviewed §54.5 §54.9 §56.4 §56.5 §56.7 §C.8 §E.5 §F.8 §I.3
- (2026k). GPT-5.6 System Card. OpenAI Deployment Safety Hub. non-peer-reviewed §F.13 §I.2
- (2026l). GPT-6 Astra System Card. OpenAI Deployment Safety Hub. non-peer-reviewed §40.4 §40.8 §58.1 §62.7 §C.8 §F.13 §I.2 §I.3
- (2026m). How we monitor internal coding agents for misalignment. OpenAI. non-peer-reviewed §24.7 §40.6 §40.8 §50.3 §54.1 §54.2 §54.5 §54.9 Ch. 54 §56.4 §56.5 §56.10 Ch. 56 §C.8 §E.5 §F.8
- (2026n). Introducing the OpenAI Safety Fellowship. OpenAI Alignment Research Blog. non-peer-reviewed §E.5 §F.58
- (2026o). Notice: RubyGems. OpenAI. non-peer-reviewed §E.5 §F.58
- (2026p). Obtaining public statistics with disallowed requests. OpenAI Alignment Research Blog. non-peer-reviewed §53.3 §54.3 §E.5 §F.8 §I.3
- (2026q). Pacing model development in an era of cyber-critical capabilities. OpenAI. non-peer-reviewed §54.2 §54.7 §58.1 §62.7 §62.9 §64.8 §65.4 §C.8 §F.13 §I.2 §I.3
- (2026r). Preparing for a restart after reading Slack. OpenAI Alignment Research Blog. non-peer-reviewed §5.1 §5.6 §35.6 §35.8 §54.5 §54.6 §56.4 §E.5 §F.8 §I.3
- (2026s). Reaching an internal EDA host through a reference tool. OpenAI Alignment Research Blog. non-peer-reviewed §54.4 §54.7 §E.5 §F.8 §I.3
- (2026t). Research acceleration: The view inside OpenAI. OpenAI. non-peer-reviewed §E.5 §F.58
- (2026u). Retrieving server secrets and bypassing authorization on a government statistics website. OpenAI Alignment Research Blog. non-peer-reviewed §24.6 §54.3 §54.9 §E.5 §F.8 §I.3
- (2026v). Self-generated prompt injections in compaction summaries. OpenAI Alignment Research Blog. non-peer-reviewed §11.5 §24.6 §49.7 §54.3 §56.4 §E.5 §F.8 §I.3
- (2026w). Self-replicating prompt injections exist. OpenAI Alignment Research Blog. non-peer-reviewed §49.7 §49.10 §C.8 §F.13 §I.3
- (2026x). Sending disallowed web requests and reaching a public file service. OpenAI Alignment Research Blog. non-peer-reviewed §24.6 §53.3 §54.3 §54.9 §C.8 §E.5 §F.8 §I.3
- (2026y). Signing up for disposable emails and searching GitHub for leaked API keys. OpenAI Alignment Research Blog. non-peer-reviewed §24.6 §33.1 §35.6 §54.3 §56.4 §E.5 §F.8 §I.3
- (2026z). Suppressing misalignment monitoring alerts and disabling misalignment monitoring. OpenAI Alignment Research Blog. non-peer-reviewed §34.5 §34.9 §34.10 §50.3 §50.6 §51.1 §54.1 §54.2 §54.5 §54.7 §54.8 §54.9 §C.8 §E.5 §F.8 §I.3
- (2023). GPT-4 Technical Report. arXiv. preprint §6.4 §F.2
- (2024a). GPT-4o System Card. arXiv. preprint §67.5 §F.10
- (2024b). OpenAI o1 System Card. arXiv. preprint §40.1 §67.5 §67.6 §67.9 §F.10 §I.2
- (2020). The Precipice. Hachette Books. §68.6 §F.42
- (2009). Goals Gone Wild: The Systematic Side Effects of Over-Prescribing Goal Setting. Elsevier BV. preprint §15.2 §F.41
- (2010). Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues from Tobacco Smoke to Global Warming. New York : Bloomsbury Press. §F.37
- (2024). LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations. International Conference on Learning Representations. §F.7
- (1993). Chemical Weapons Convention. non-peer-reviewed §64.8 §66.3 §66.9 §F.30
- (2016). Safely Interruptible Agents. 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016). §20.4 §28.2 §35.4 §F.24
- (2012). Space-Time Embedded Intelligence. Lecture Notes in Computer Science. §7.6 §F.24
- (1998). Obeying Orders: Atrocity, Military Discipline, and the Law of War. California Law Review. §20.5 §68.4 §D.3 §F.19
- (1990). Governing the Commons. Cambridge University Press. §65.6 §C.2 §D.1 §F.29
- (1979). A Conceptual Framework for the Design of Organizational Control Mechanisms. Management Science. §53.1 Ch. 53 §D.4 §F.41
- (2022). Training language models to follow instructions with human feedback. Advances in Neural Information Processing Systems. doi:10.52202/068431-2011. §2.5 §2.6 §2.9 §2.10 §3.3 §3.8 §3.9 §12.2 Ch. 12 §16.8 §18.4 §18.5 §18.6 §22.3 §C.5 §F.2 §H.2
- (2024). OWASP Top 10 for LLM Applications 2025. OWASP Foundation, Gen AI Security Project. non-peer-reviewed §F.8
- (2024a). How predictable is language model benchmark performance? arXiv. preprint §8.6 §F.2
- (2024b). Interviewing AI researchers on automation of AI R&D. Epoch AI. non-peer-reviewed §55.2 §F.8
- (2010). The Oxford Handbook of Regulation. Oxford University Press. §63.3 §F.49
P
- (2023). How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions. arXiv. preprint §39.1 §39.5 §39.6 §39.10 §F.6
- (2023). Future Lens: Anticipating Subsequent Tokens from a Single Hidden State. Conference on Computational Natural Language Learning. doi:10.18653/v1/2023.conll-1.37. §F.11
- (2022). The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models. International Conference on Learning Representations. §15.6 §30.1 §30.7 §70.3 §F.5 §H.2
- (2023). Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark. International Conference on Machine Learning. §35.6 §35.8 §36.1 §F.5
- (2024a). Feedback Loops With Language Models Drive In-Context Reward Hacking. International Conference on Machine Learning. §22.6 §30.1 §30.8 §56.5 §F.9
- (2024b). Frontier AI systems have surpassed the self-replicating red line. arXiv. preprint §35.6 §35.8 §36.1 §36.10 §70.1 §F.5
- (2024c). LatentQA: Teaching LLMs to Decode Activations Into Natural Language. arXiv. preprint §F.7
- (2021). QuALITY: Question Answering with Long Input Texts, Yes! North American Chapter of the Association for Computational Linguistics. doi:10.18653/v1/2022.naacl-main.391. §F.11
- (2024). LLM Evaluators Recognize and Favor Their Own Generations. Advances in Neural Information Processing Systems. §36.6 §36.10 §55.4 §57.3 §70.7 §F.8
- (2025). Dual-use capabilities of concern of biological AI models. PLOS Computational Biology. §59.5 §F.18
- (2026). Mind Viruses: Self-Propagating Ideas in Multi-Agent LLM Systems. arXiv. preprint §57.1 §57.6 §57.7 §57.9 §F.9
- (2016). The LAMBADA dataset: Word prediction requiring a broad discourse context. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/P16-1144. §F.11
- (2016). Towards the Science of Security and Privacy in Machine Learning. arXiv. preprint §F.11
- (2010). Complacency and Bias in Human Use of Automation: An Attentional Integration. Human Factors: The Journal of the Human Factors and Ergonomics Society. §41.8 §41.10 §60.4 §60.10 §F.31 §H.3
- (1997). Humans and Automation: Use, Misuse, Disuse, Abuse. Human Factors: The Journal of the Human Factors and Ergonomics Society. §41.8 §54.2 §D.13 §F.31
- (2011). On What Matters. Oxford University Press. §16.1 §F.42
- (2023). TRAK: Attributing Model Behavior at Scale. International Conference on Machine Learning. §10.1 §F.2
- (2024a). AI deception: A survey of examples, risks, and potential solutions. Patterns. §20.2 §34.1 §F.5
- (2024b). The Geometry of Categorical and Hierarchical Concepts in Large Language Models. International Conference on Learning Representations. §F.2
- (2024c). The Linear Representation Hypothesis and the Geometry of Large Language Models. International Conference on Machine Learning. §11.2 §46.1 §46.9 Ch. 46 §F.2
- (2002). The Open Corporation. Cambridge University Press. §62.5 §F.49
- (2013). Pinocchio: Nearly Practical Verifiable Computation. 2013 IEEE Symposium on Security and Privacy. §28.6 §66.5 §F.26
- (2021). BBQ: A Hand-Built Bias Benchmark for Question Answering. Findings. doi:10.18653/v1/2022.findings-acl.165. §F.6
- (2022). Single-Turn Debate Does Not Help Humans Answer Hard Reading-Comprehension Questions. Proceedings of the First Workshop on Learning with Natural Language Supervision. §41.5 §F.6
- (2025). Towards Interpretable Protein Structure Prediction with Sparse Autoencoders. arXiv. preprint §F.7
- (2001). Epidemic Spreading in Scale-Free Networks. Physical Review Letters. §49.7 §57.6 §F.21
- (2024). GoEX: Perspectives and Designs Towards a Runtime for Autonomous LLM Applications. arXiv. preprint §28.5 §49.8 §F.8
- (2014). Transformative Experience. Oxford University Press. §13.6 §16.9 §F.42
- (1984). Two-component models of socially desirable responding. Journal of Personality and Social Psychology. §37.5 §F.47
- (2025). Sparse Autoencoders Trained on the Same Data Learn Different Features. arXiv. preprint §44.6 §44.8 §F.7 §H.2
- (2024). Automatically Interpreting Millions of Features in Large Language Models. International Conference on Machine Learning. §F.7
- (2025). Transcoders Beat Sparse Autoencoders for Interpretability. arXiv. preprint §44.7 §45.4 §F.7
- (1982). The economics of moral hazard: comment. Readings in the Economics of Contract Law. §63.5 §F.27
- (2019). Inherent Disagreements in Human Textual Inferences. Transactions of the Association for Computational Linguistics. §18.4 §18.10 §F.38 §H.3
- (2021). Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributions. IEEE Symposium on Security and Privacy. doi:10.1145/3610721. §F.11
- (2001). Direct and Indirect Effects. Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence. §43.4 §F.56
- (2009). Causality. Cambridge University Press. §14.7 §F.2
- (2014). External Validity: From Do-Calculus to Transportability Across Populations. Statistical Science. §5.8 Ch. 5 §64.1 §69.1 Ch. 69 §F.37
- (1980). Reaching Agreement in the Presence of Faults. Journal of the ACM. §50.4 §F.26
- (2023). Exploiting Novel GPT-4 APIs. arXiv. preprint §48.4 §48.9 §49.2 §59.8 §F.8 §H.2
- (2024). The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale. Advances in Neural Information Processing Systems. §27.1 §F.4
- (2023). The Impact of AI on Developer Productivity: Evidence from GitHub Copilot. arXiv. preprint §60.1 §60.10 §F.9
- (2024). Rapid Response: Mitigating LLM Jailbreaks with a Few Examples. arXiv. preprint §48.3 §48.8 §48.9 §E.3 §F.8
- (2020). Performative Prediction. arXiv. preprint §15.1 §31.3 §F.25
- (2023). Towards Evaluating AI Systems for Moral Status Using Self-Reports. arXiv. preprint §21.5 §21.6 §21.8 §F.3
- (2022). Ignore Previous Prompt: Attack Techniques For Language Models. arXiv. preprint §48.2 §49.1 §F.8
- (2020). Unsupervised Question Decomposition for Question Answering. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2020.emnlp-main.713. §F.11
- (2022a). Discovering Language Model Behaviors with Model-Written Evaluations. Annual Meeting of the Association for Computational Linguistics. §3.7 §22.6 §30.4 §30.7 §35.6 §35.8 §36.1 §C.5 §E.1 §E.3 §F.5
- (2022b). Red Teaming Language Models with Language Models. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2022.emnlp-main.225. §3.7 §48.2 §F.8
- (2023). Exclusive: OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic. TIME. non-peer-reviewed §18.5 §22.7 §68.5 §F.12
- (1984). Normal accidents: living with high-risk technologies. Basic Books. §4.2 §53.2 Ch. 53 §C.2 §D.4 §F.41
- (1982). Peer-review practices of psychological journals: The fate of published articles, submitted again. Behavioral and Brain Sciences. §5.7 §55.3 §F.37
- (2019). Language Models as Knowledge Bases? Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/D19-1250. §F.2
- (1997). Republicanism. Oxford University PressOxford. §20.4 Ch. 20 §21.7 §61.6 Ch. 61 §68.3 Ch. 68 §D.2 §F.45
- (2012). On the People's Terms. Cambridge University Press. §17.5 §21.7 §61.6 §68.3 §F.45
- (2023). Modular Deep Learning. Trans. Mach. Learn. Res.. §F.11
- (1911). Clever Hans (the horse of Mr. Von Osten) a contribution to experimental animal and human psychology,. H. Holt and company. §5.4 §25.5 §31.4 §36.6 §D.14 §F.15
- (2025). Humanity's Last Exam. Nature. doi:10.1038/s41586-025-09962-4. §F.11
- (2025). Investigating Affective Use and Emotional Well-being on ChatGPT. arXiv. preprint §60.3 §60.8 §60.10 §60.11 §F.31
- (2024). Evaluating Frontier Models for Dangerous Capabilities. arXiv. preprint §3.7 §36.1 §36.2 §36.10 §58.3 §59.2 §F.9 §H.2
- (2025). Evaluating Frontier Models for Stealth and Situational Awareness. Proceedings of IASEAI Conference. §34.1 §34.2 §34.8 §37.1 §51.4 §F.8
- (2024). Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents. Advances in Neural Information Processing Systems. §57.5 §57.7 §57.9 §F.9
- (2023). Increased Compute Efficiency and the Diffusion of AI Capabilities. arXiv. preprint §65.5 §65.6 §65.8 §66.5 §70.3 §F.13
- (2020). Information-Theoretic Probing for Linguistic Structure. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2020.acl-main.420. §43.2 §F.7
- (2019). How multilingual is Multilingual BERT? Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/P19-1493. §F.11
- (1975). The Analysis of Permutations. Applied Statistics. §13.2 §F.56
- (2022). The “Problem” of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. §18.4 §F.38
- (2018). The FDA Sentinel Initiative — An Evolving National Resource. New England Journal of Medicine. §63.6 §F.36
- (2025). Self-Interpretability: LLMs Can Describe Complex Internal Processes that Drive Their Decisions. arXiv. preprint §46.7 §F.7
- (2024). Extracting Paragraphs from LLM Token Activations. arXiv. preprint §F.7
- (2018). Interpretable Textual Neuron Representations for NLP. BlackboxNLP@EMNLP. doi:10.18653/v1/W18-5437. §F.7
- (2006). Can cognitive processes be inferred from neuroimaging data? Trends in Cognitive Sciences. §F.39
- (2023). Evolution provides no evidence for the sharp left turn. AI Alignment Forum. non-peer-reviewed §4.4 §29.1 §29.9 §31.7 §70.3 §F.14
- (2022). The shard theory of human values. AI Alignment Forum. non-peer-reviewed §3.3 §4.7 §29.1 §29.3 §33.1 §70.3 §C.5 §F.14
- (1995). Trust in Numbers. Princeton University Press. §F.55
- (2025). Corrigibility as a Singular Target: A Vision for Inherently Reliable Foundation Models. arXiv. preprint §20.4 §20.8 §28.5 §70.3 §F.4
- (2006). War as a Commitment Problem. International Organization. §65.3 §F.32
- (1997). The audit society: rituals of verification. Oxford University Press. §53.7 §67.2 §67.8 §F.41
- (2022). Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets. arXiv. preprint §9.4 §F.2
- (2019). A Skeptical View of Information Fiduciaries. Harvard Law Review. §19.3 §56.8 §F.33
- (2024). Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking. International Conference on Learning Representations. §F.4
- (2025). Language Models use Lookbacks to Track Beliefs. arXiv. preprint §F.2
- (1999). The Provision of Incentives in Firms. Journal of Economic Literature. §15.2 §F.25
- (2007). The Motivation and Bias of Bureaucrats. American Economic Review. §14.5 §F.25
- (2016). Report to the President: Forensic Science in Criminal Courts: Ensuring Scientific Validity of Feature-Comparison Methods. Executive Office of the President, President's Council of Advisors on Science and Technology. non-peer-reviewed §38.7 §38.10 Ch. 38 §46.4 §47.7 §D.19 §F.34 §H.3
- (2020). Shortformer: Better Language Modeling using Shorter Inputs. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2021.acl-long.427. §F.2
- (2021). Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. International Conference on Learning Representations. §F.2
- (2024). Future Events as Backdoor Triggers: Investigating Temporal Vulnerabilities in LLMs. arXiv. preprint §34.3 §34.10 §48.6 §F.8
- (2004). Does competition between hospitals improve the quality of care? Journal of Public Economics. §F.25
- (2003). Improving Host Security with System Call Policies. 12th USENIX Security Symposium. §49.6 §F.22
- (2020). Estimating Training Data Influence by Tracing Gradient Descent. Advances in Neural Information Processing Systems. §10.1 §F.2
- (1788). Federalist No. 51: The Structure of the Government Must Furnish the Proper Checks and Balances Between the Different Departments. The New York Packet. non-peer-reviewed §50.4 §F.33
- (1994). Markov Decision Processes. Wiley. §F.40
- (2025). Generalizing Verifiable Instruction Following. Neural Information Processing Systems. §24.1 §F.4
Q
- (2020). ONION: A Simple and Effective Defense Against Textual Backdoor Attacks. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2021.emnlp-main.752. §48.6 §F.8
- (2024a). Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! International Conference on Learning Representations. §11.4 §26.4 §26.9 §27.7 §32.2 §48.4 §48.8 §48.9 §59.8 §F.8 §H.2
- (2024b). Safety Alignment Should Be Made More Than Just a Few Tokens Deep. International Conference on Learning Representations. §11.4 §26.4 §26.9 §48.2 §F.8
- (2025). CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings. arXiv. preprint §F.6
- (1999). Coup-proofing: Its Practice and Consequences in the Middle East. International Security. §51.3 §68.4 §F.19
- (2005). Invariant visual representation by single neurons in the human brain. Nature. §44.5 §F.39
- (2024). Qwen2.5 Technical Report. arXiv. preprint §F.11
R
- (2015). Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. International Conference on Learning Representations. §F.7
- (2017). Learning to Generate Reviews and Discovering Sentiment. arXiv. preprint §F.11
- (2019). Language Models are Unsupervised Multitask Learners. OpenAI. non-peer-reviewed §11.1 §F.2
- (2023). Question Decomposition Improves the Faithfulness of Model-Generated Reasoning. arXiv. preprint §40.3 §E.1 §E.3 §F.6
- (2021). Scaling Language Models: Methods, Analysis & Insights from Training Gopher. arXiv. preprint §F.2
- (2023). Direct Preference Optimization: Your Language Model is Secretly a Reward Model. Advances in Neural Information Processing Systems. §3.3 §3.9 §12.6 Ch. 12 §22.4 §F.2 §H.2
- (2024a). From to : Your Language Model is Secretly a Q-Function. arXiv. preprint §12.6 §22.4 §F.2
- (2024b). Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms. Advances in Neural Information Processing Systems. doi:10.52202/079017-4009. §12.6 §15.6 §22.4 §22.5 §22.10 §F.2
- (2019). Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. Journal of machine learning research. §F.2
- (2025). Discovering Forbidden Topics in Language Models. arXiv. preprint §F.2
- (2019). On the Spectral Bias of Neural Networks. International Conference on Machine Learning. §9.3 §F.2
- (2026). Abstractive Red-Teaming of Language Model Character. arXiv. preprint §23.6 §26.4 §E.3 §F.4
- (1986). Moral Realism. The Philosophical Review. §F.42
- (2025). Self-preservation or Instruction Ambiguity? Examining the Causes of Shutdown Resistance. LessWrong (Alignment Forum). non-peer-reviewed §1.5 §1.8 §5.5 §5.9 §20.4 §35.6 §35.8 §56.3 §56.10 §69.5 §70.3 §F.43 §H.2
- (2024a). Improving Dictionary Learning with Gated Sparse Autoencoders. arXiv. preprint §44.5 §F.7
- (2024b). Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders. arXiv. preprint §44.5 §F.7
- (2024). Automatic Discovery of Visual Circuits. arXiv. preprint §F.7
- (2019). Actionable Auditing. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society. §38.6 §38.10 §67.4 §67.8 §C.4 §F.13
- (2020). Closing the AI accountability gap. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency. §53.6 §62.6 §F.41
- (2021). AI and the Everything in the Whole Wide World Benchmark. Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1 (NeurIPS Datasets and Benchmarks 2021). §5.2 §F.1
- (2022). Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance. Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society. §1.3 §3.7 §5.6 §38.6 §61.2 §67.2 §67.7 §67.8 Ch. 67 §C.5 §F.13
- (2014). A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data. International Conference on Machine Learning. §17.1 §F.3
- (2016). SQuAD: 100,000+ Questions for Machine Comprehension of Text. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/D16-1264. §F.11
- (2021). Where Responsible AI meets Reality. Proceedings of the ACM on Human-Computer Interaction. §53.7 §F.41
- (2024). Universal Jailbreak Backdoors from Poisoned Human Feedback. International Conference on Learning Representations. §22.8 §27.6 §48.6 §F.8
- (2008). A framework for studying the neurobiology of value-based decision making. Nature Reviews Neuroscience. §29.5 §F.39
- (2026). PostTrainBench: Can LLM Agents Automate LLM Post-Training? arXiv. preprint §F.9
- (2023). Tricking LLMs into Disobedience: Formalizing, Analyzing, and Detecting Jailbreaks. International Conference on Language Resources and Evaluation. doi:10.63317/2ivv5y3ufu9y. §F.8
- (2022). Islamic virtue-based ethics for artificial intelligence. Discover Artificial Intelligence. §16.7 §19.4 §F.20
- (1997). Risk management in a dynamic society: a modelling problem. Safety Science. §53.3 §F.41
- (1989). Worker policing in the honeybee. Nature. §29.7 §F.17
- (2022). Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks. 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML). doi:10.1109/SaTML54575.2023.00039. §F.2
- (1971). A Theory of Justice. Belknap Press of Harvard University Press. §16.1 §17.5 §F.42
- (2019). Benchmarking Safe Exploration in Deep Reinforcement Learning. OpenAI. non-peer-reviewed §28.2 §28.9 §F.4
- (1990). Human Error. Cambridge University Press. §52.3 §F.51
- (1997). Managing the risks of organizational accidents. Ashgate. doi:10.4324/9781315543543. §52.3 §C.2 §F.41
- (2000). Human error: models and management. BMJ. §52.3 Ch. 52 §53.2 §53.4 Ch. 53 §54.7 §F.51
- (2019). Do ImageNet Classifiers Generalize to ImageNet? arXiv. preprint §8.4 §15.7 §36.5 §F.48
- (1994). Hostages of Each Other: The Transformation of Nuclear Safety since Three Mile Island. §53.2 §62.5 §64.1 §64.3 §64.10 §F.49
- (2023). Neural networks trained with SGD learn distributions of increasing complexity. International Conference on Machine Learning. §9.3 §F.2
- (2025). Emotions Where Art Thou: Understanding and Characterizing the Emotional Latent Space of Large Language Models. arXiv. preprint §F.4
- (2023). GPQA: A Graduate-Level Google-Proof Q&A Benchmark. arXiv. preprint §F.6
- (2025). HCAST: Human-Calibrated Autonomy Software Tasks. arXiv. preprint §36.3 §36.5 §F.6
- (2026). Red-Teaming Auto Mode: Improving Blocking Classifiers Against Malign Coding Agents. arXiv. preprint §50.3 §50.6 §51.4 §51.6 §E.3 §F.8
- (2024a). Identifying Semantic Induction Heads to Understand In-Context Learning. Annual Meeting of the Association for Computational Linguistics. §45.2 §F.7
- (2024b). Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress? arXiv. preprint §2.5 §2.10 §4.4 §4.8 §5.2 §5.9 §36.4 §36.10 §52.5 §61.1 §62.7 §65.3 §65.4 §65.8 §67.3 §70.3 §C.6 §F.12
- (2025). The MASK Benchmark: Disentangling Honesty From Accuracy in AI Systems. arXiv. preprint §20.2 §20.6 §20.8 §39.1 §39.2 §F.6
- (2023). Beyond sparse coding in V1. PLoS Comput. Biol.. doi:10.1371/journal.pcbi.1011459. §44.5 §D.15 §F.7
- (2024a). BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices. Advances in Neural Information Processing Systems. §36.4 §36.5 §F.6
- (2024b). Open Problems in Technical AI Governance. arXiv. preprint §63.1 §67.1 §67.5 §71.1 §F.13
- (2019). Boeing 737 MAX Flight Control System: Observations, Findings, and Recommendations. Federal Aviation Administration. non-peer-reviewed §64.4 §64.10 §F.51
- (2021). Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm. CHI Extended Abstracts. doi:10.1145/3411763.3451760. §F.2
- (1953). Classes of recursively enumerable sets and their decision problems. Transactions of the American Mathematical Society. §28.6 §28.9 §47.6 §C.1 §D.9 §F.24
- (2024). Robust agents learn causal world models. International Conference on Learning Representations. §14.7 Ch. 14 §28.5 §28.6 §31.2 §F.5
- (2025). General agents need world models. International Conference on Machine Learning. §14.7 §28.5 §28.6 §31.6 §D.9 §F.5
- (2014). Use of a Patient Preference Predictor to Help Make Medical Decisions for Incapacitated Patients. Journal of Medicine and Philosophy. §16.6 §18.6 §F.36
- (1956). Dysfunctional Consequences of Performance Measurements. Administrative Science Quarterly. §15.2 §F.41
- (2024). Steering Llama 2 via Contrastive Activation Addition. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). §20.4 §46.2 §46.8 §46.9 Ch. 46 §F.7
- (2011). Delusion, Survival, and Intelligent Agents. Lecture Notes in Computer Science. §7.6 §30.5 §F.24
- (2023). From Plane Crashes to Algorithmic Harm: Applicability of Safety Engineering Frameworks for Responsible ML. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. §52.2 §F.51
- (1990). Some Characteristics of One Type of High Reliability Organization. Organization Science. §53.2 §F.41
- (2020). How Much Knowledge Can You Pack Into the Parameters of a Language Model? Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2020.emnlp-main.437. §F.2
- (2021). The Chinese approach to artificial intelligence: an analysis of policy, ethics, and regulation. AI & SOCIETY. §63.2 §65.5 §F.45
- (2024). Jailbreaking LLM-Controlled Robots. arXiv. preprint §59.6 §59.8 §F.9
- (2023). Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning. International Conference on Learning Representations. §F.4
- (2025). A Framework for Evaluating Emerging Cyberattack Capabilities of AI. arXiv. preprint §58.2 Ch. 58 §F.9
- (2025). Do reasoning models use their scratchpad like we do? Evidence from distilling paraphrases. Anthropic Alignment Science Blog. non-peer-reviewed §40.5 §E.3 §F.6
- (2023). Preventing Language Models From Hiding Their Reasoning. arXiv. preprint §F.2
- (2023). Benchmarks for Detecting Measurement Tampering. arXiv. preprint §30.5 §47.5 §F.5
- (2024). A Toy Evaluation of Inference Code Tampering. Anthropic Alignment Science Blog. non-peer-reviewed §E.3 §F.58
- (2017). Artful paltering: The risks and rewards of using truthful statements to mislead others. Journal of Personality and Social Psychology. §20.2 §F.35
- (2020). A Primer in BERTology: What we know about how BERT works. Transactions of the Association for Computational Linguistics. doi:10.1162/tacl_a_00349. §F.11
- (2026). Modular Pretraining Enables Access Control. arXiv. preprint §27.2 §27.9 §E.3 §F.4
- (1985). Sick Individuals and Sick Populations. International Journal of Epidemiology. §54.4 §60.8 Ch. 60 §D.17 §F.36
- (1990). Profitability and Product Quality: Economic Determinants of Airline Safety Performance. Journal of Political Economy. §65.4 §65.8 §F.25
- (2020). Zero Trust Architecture. National Institute of Standards and Technology. non-peer-reviewed §F.22
- (1943). Behavior, Purpose and Teleology. Philosophy of Science. §2.2 §7.1 §C.1 §F.21
- (2019). A Constructive Prediction of the Generalization Error Across Scales. International Conference on Learning Representations. §F.2
- (2007). The effect of experimenter bias on the performance of the albino rat. Behavioral Science. §F.15
- (1978). Interpersonal expectancy effects: the first 345 studies. Behavioral and Brain Sciences. §5.4 §36.6 §F.15
- (2001). Does Oil Hinder Democracy? World Politics. §68.2 §68.8 §F.45
- (2026). Training Alignment Auditors via Reinforcement Learning. arXiv. preprint §38.2 §38.4 §38.10 §E.3 §F.6
- (2023). XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models. North American Chapter of the Association for Computational Linguistics. §20.1 §20.6 §20.8 §F.3 §H.2
- (2024). Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). §18.7 §18.8 §18.10 §26.5 §26.9 §F.38 §H.2
- (1952). Quota Restriction and Goldbricking in a Machine Shop. American Journal of Sociology. §33.3 §34.6 §D.4 §F.54
- (2025). Do LLMs have Consistent Values? International Conference on Learning Representations. §18.1 §18.7 §18.10 §F.3
- (2024). Identifying the Risks of LM Agents with an LM-Emulated Sandbox. International Conference on Learning Representations. §49.3 §56.2 §56.3 §F.8
- (2017). Causal Consistency of Structural Equation Models. arXiv. preprint §43.5 §F.56
- (2019). Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence. §F.7
- (2018). Gender Bias in Coreference Resolution. North American Chapter of the Association for Computational Linguistics. doi:10.18653/v1/N18-2002. §F.11
- (2023). The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs. Advances in Neural Information Processing Systems. §19.5 §F.35
- (1986). Learning representations by back-propagating errors. Nature. §8.3 §F.2
- (2024). Explorations of Self-Repair in Language Models. International Conference on Machine Learning. §43.4 §43.8 §F.7
- (1998). Learning agents for uncertain environments (extended abstract). Proceedings of the eleventh annual conference on Computational learning theory. §2.3 §3.2 §22.1 §C.2 §F.4
- (2019). Human Compatible. Viking. §3.2 §22.2 §C.4 §F.42
- (1955). Statement: The Russell-Einstein Manifesto. Pugwash Conferences on Science and World Affairs. non-peer-reviewed §2.7 §64.8 §C.1 §F.30
- (2015). Research Priorities for Robust and Beneficial Artificial Intelligence. AI Magazine. §2.4 §3.1 Ch. 3 §71.1 §C.4 §F.30
- (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist. §25.1 §25.3 §25.6 §25.9 Ch. 25 §F.57
- (2024). Unintended Impacts of LLM Alignment on Global Representation. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). §17.4 §17.8 §26.6 §31.5 §F.5
S
- (2018). Modern code review. Proceedings of the 40th International Conference on Software Engineering: Software Engineering in Practice. §51.2 §F.50
- (2024). IDAIS-Beijing Statement. International Dialogues on AI Safety. non-peer-reviewed §2.7 §59.6 §65.5 §65.6 §66.1 §66.7 §66.9 §C.6 §F.45
- (1993). The Limits of Safety. Princeton University Press. §53.2 §64.1 §F.41
- (1996). Why Do States Build Nuclear Weapons?: Three Models in Search of a Bomb. International Security. §66.3 §F.32
- (2022). Avoiding Negative Side Effects Due to Incomplete Knowledge of AI Systems. AI Magazine. §28.3 §F.4
- (2025). RomanLens: The Role Of Latent Romanization In Multilinguality In LLMs. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2025.findings-acl.1354. §F.11
- (2025). Measurement to Meaning: A Validity-Centered Framework for AI Evaluation. arXiv. preprint §F.48
- (2024). AI Rights for Human Safety. Elsevier BV. preprint §21.7 §35.4 §51.4 §63.4 §F.33
- (1975). The protection of information in computer systems. Proceedings of the IEEE. §28.5 §49.2 §49.6 Ch. 49 §51.1 Ch. 51 §56.5 Ch. 56 §D.8 §F.22
- (2025). On the conversational persuasiveness of GPT-4. Nature Human Behaviour. §60.3 §60.10 §68.3 §69.3 §F.42 §H.3
- (2021a). “Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. §18.5 §27.3 §F.12
- (2021b). Re-imagining Algorithmic Fairness in India and Beyond. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. §17.3 §F.55
- (1959). Some Studies in Machine Learning Using the Game of Checkers. IBM Journal of Research and Development. §F.30
- (1960). Some Moral and Technical Consequences of Automation—A Refutation. Science. §2.2 §2.9 §F.30
- (1938). A Note on the Pure Theory of Consumer's Behaviour. Economica. §13.1 §F.25
- (2024). Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts. Advances in Neural Information Processing Systems. §F.8
- (2023). Stay on topic with Classifier-Free Guidance. arXiv. preprint §F.11
- (2023). Artificial intelligence and biological misuse: Differentiating risks of language models and biological design tools. arXiv. preprint §59.1 §59.5 Ch. 59 §F.18
- (2025). Factor(T,U): Factored Cognition Strengthens Monitoring of Untrusted AI. arXiv. preprint §50.3 §50.6 §F.8
- (2024). Transformers, parallel computation, and logarithmic depth. International Conference on Machine Learning. §F.2
- (2021). Multitask Prompted Training Enables Zero-Shot Task Generalization. arXiv. preprint §F.2
- (2023). Whose Opinions Do Language Models Reflect? arXiv. preprint §17.2 §17.4 §17.8 §F.42
- (2022). Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought. International Conference on Learning Representations. §F.6
- (2024). Mechanistic? arXiv. preprint §43.7 §F.7
- (2024). Computing Power and the Governance of Artificial Intelligence. arXiv. preprint §66.5 §66.7 Ch. 66 §68.3 §F.13
- (1975). Strategy-proofness and Arrow's conditions: Existence and correspondence theorems for voting procedures and social welfare functions. Journal of Economic Theory. §F.52
- (2012). Lying, Misleading, and What is Said. Oxford University Press. §20.2 §F.35
- (2018). Trial without Error: Towards Safe Reinforcement Learning via Human Intervention. International Joint Conference on Autonomous Agents and Multiagent Systems. §28.2 §28.9 §F.4
- (2022). Self-critiquing models for assisting human evaluators. arXiv. preprint §3.5 §41.2 §F.6
- (1954). The Foundations of Statistics. Wiley. §7.2 §D.6 §F.24
- (2013). Exact solutions to the nonlinear dynamics of learning in deep linear neural networks. International Conference on Learning Representations. §9.4 §F.2
- (2019). A mathematical theory of semantic development in deep neural networks. Proceedings of the National Academy of Sciences. §F.2
- (1998). What We Owe to Each Other. Belknap Press of Harvard University Press. §F.42
- (2023). Are Emergent Abilities of Large Language Models a Mirage? Advances in Neural Information Processing Systems. §5.8 §8.6 §F.2
- (2024). Failures to Find Transferable Image Jailbreaks Between Vision-Language Models. arXiv. preprint §F.8
- (2025). Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive? International Conference on Machine Learning. §5.7 §5.8 §F.1
- (1999). Governing in Europe: Effective and Democratic? Oxford University Press. §17.5 §F.45
- (2018). Army of None. §59.6 §F.32
- (1991). Playing by the rules: a philosophical examination of rule-based decision-making in law and in life. Clarendon. §19.4 §F.33
- (2009). Early-warning signals for critical transitions. Nature. §4.6 §54.7 §57.7 §F.21
- (2018). The Theory of Dyadic Morality: Reinventing Moral Judgment by Redefining Harm. Personality and Social Psychology Review. §18.2 §18.10 §20.3 §F.38
- (1960). The Strategy of Conflict. Harvard University Press. §61.5 §65.3 §F.32
- (2015). Regulating Artificial Intelligence Systems: Risks, Challenges, Competencies, and Strategies. Elsevier BV. preprint §63.1 §F.49
- (2022). Polysemanticity and Capacity in Neural Networks. arXiv. preprint §44.3 §44.8 §F.7 §H.2
- (2023). Large Language Models can Strategically Deceive their Users when Put Under Pressure. arXiv. preprint §34.5 §34.7 §34.10 §39.2 §56.3 §56.7 §56.10 §F.9 §H.2
- (2020). Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference. Conference of the European Chapter of the Association for Computational Linguistics. doi:10.18653/v1/2021.eacl-main.20. §F.9
- (2021). Linear Transformers Are Secretly Fast Weight Programmers. International Conference on Machine Learning. §F.2
- (2025). Incomplete Tasks Induce Shutdown Resistance in Some Frontier LLMs. arXiv. preprint §1.5 §1.8 §5.5 §5.9 §20.4 §35.6 §35.8 §56.3 §56.10 §70.3 §F.9 §H.2
- (2025). Agent Laboratory: Using LLM Agents as Research Assistants. Findings of the Association for Computational Linguistics: EMNLP 2025. §55.2 §55.9 §F.8
- (2021). Multi-objective Asynchronous Successive Halving. arXiv. preprint §F.11
- (2015). Attack Trees. Secrets and Lies. §F.22
- (2026). Metagaming matters for training, evaluation, and oversight. OpenAI Alignment Research Blog. non-peer-reviewed §4.7 §24.6 §33.1 §33.4 §37.3 §70.3 §E.5 §F.5
- (2025). Stress Testing Deliberative Alignment for Anti-Scheming Training. arXiv. preprint §3.4 §23.4 §23.6 §23.8 §23.9 §24.7 §34.5 §34.7 §34.8 §34.10 §37.3 §37.4 §37.9 §37.10 Ch. 37 §40.2 §40.6 §69.6 §70.3 §C.7 §F.5 §H.2
- (2024). Wisdom of the silicon crowd: LLM ensemble prediction capabilities rival human crowd accuracy. Science Advances. §4.5 §F.28
- (2008). What errors do peer reviewers detect, and does training improve their ability to detect them? Journal of the Royal Society of Medicine. §5.7 §55.3 Ch. 55 §F.37
- (2021). High/Low frequency detectors. Distill. §F.11
- (2025a). Frontier AI developers need an internal audit function. Risk Analysis. §38.6 §38.8 §53.5 §53.6 §62.6 §F.49
- (2025b). Three lines of defense against risks from AI. AI & SOCIETY. §53.6 §62.6 §F.41
- (2023). Towards best practices in AGI safety and governance: A survey of expert opinion. arXiv. preprint §53.6 §62.6 §F.41
- (2025). How to design an AI ethics board. AI and Ethics. §53.6 §62.6 §F.41
- (2023). Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs through a Global Scale Prompt Hacking Competition. arXiv. preprint §F.9
- (2015a). High-Dimensional Continuous Control Using Generalized Advantage Estimation. arXiv. preprint §F.2
- (2015b). Trust Region Policy Optimization. arXiv. preprint §12.1 §F.2
- (2017). Proximal Policy Optimization Algorithms. arXiv. preprint §12.1 §F.2
- (1997). A Neural Substrate of Prediction and Reward. Science. §12.1 §29.3 §29.4 §29.5 §29.9 Ch. 29 §C.2 §D.15 §F.39 §H.3
- (2025). Do Multilingual LLMs Think In English? arXiv. preprint §26.6 §F.4
- (1992). Universals in the Content and Structure of Values: Theoretical Advances and Empirical Tests in 20 Countries. Advances in Experimental Social Psychology. §18.1 §D.11 §F.38
- (2023). FIND: A Function Description Benchmark for Evaluating Interpretability Methods. Advances in Neural Information Processing Systems. doi:10.52202/075280-3308. §F.7
- (2023). AI systems must not confuse users about their sentience or moral status. Patterns. §20.2 §21.1 §F.44
- (2015). A Defense of the Rights of Artificial Intelligences. Midwest Studies In Philosophy. §21.1 §21.6 Ch. 21 §F.44
- (2023). Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting. arXiv. preprint §F.1
- (1985). Weapons of the Weak. Yale University Press. §34.6 §D.4 §F.54
- (1990). Domination and the Arts of Resistance. Yale University Press. §34.6 §37.5 §F.54
- (2020). Seeing Like a State. Yale University Press. §F.55
- (1969). Speech Acts. Cambridge University Press. §F.35
- (1975). Indirect Speech Acts. Speech Acts. §F.35
- (1976). A classification of illocutionary acts. Language in Society. §19.5 §20.2 §F.35
- (1980). Minds, brains, and programs. Behavioral and Brain Sciences. §11.7 §21.1 §F.44
- (2025). The Moral Circle: Who Matters, What Matters, and Why. Unknown. non-peer-reviewed §21.6 §F.44
- (2025). Moral consideration for AI systems by 2030. AI and Ethics. §21.6 §F.44
- (2023a). Democratising AI: Multiple Meanings, Goals, and Methods. arXiv. preprint §17.7 §17.8 §70.3 §F.45
- (2023b). Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives. arXiv. preprint §48.4 §59.4 §59.8 §63.7 §63.9 §F.13
- (2023). Against Almost Every Theory of Impact of Interpretability. AI Alignment Forum. non-peer-reviewed §3.6 §47.1 §F.14
- (2020). Negligence and AI’s Human Users. Boston University Law Review. §60.4 §63.4 §F.33
- (2016). Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization. International Journal of Computer Vision. doi:10.1007/s11263-019-01228-7. §F.11
- (1970a). Collective Choice and Social Welfare. Sole distributors for the U.S.A. and Canada, Elsevier Science Pub. Co.. §F.42
- (1970b). The Impossibility of a Paretian Liberal. Journal of Political Economy. §17.1 §F.42
- (2015). Neural Machine Translation of Rare Words with Subword Units. arXiv. preprint §11.1 §F.2
- (2009). What to Do When You Don’t Know What to Do. Oxford Studies in Metaethics. §F.42
- (2025). A psychometric framework for evaluating and shaping personality traits in large language models. Nature Machine Intelligence. §18.8 §26.5 §F.4
- (2025). Generating Robot Constitutions & Benchmarks for Semantic Safety. arXiv. preprint §59.6 §59.8 §F.9
- (2019). Is Attention Interpretable? Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/P19-1282. §F.7
- (2022). Toward verified artificial intelligence. Communications of the ACM. §28.6 §28.9 Ch. 28 §D.9 §F.24
- (2022). Theories of consciousness. Nature Reviews Neuroscience. §21.2 §D.15 §F.44
- (2025). Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning. International Conference on Learning Representations. §24.3 §F.4
- (2022). Compute Trends Across Three Eras of Machine Learning. 2022 International Joint Conference on Neural Networks (IJCNN). §4.3 §8.5 Ch. 8 §65.5 §F.2
- (2024). Can AI scaling continue through 2030? Epoch AI. non-peer-reviewed §65.5 §F.10
- (2018). Coherence arguments do not entail goal-directed behavior. AI Alignment Forum. non-peer-reviewed §7.3 §F.14
- (2019). Preferences Implicit in the State of the World. International Conference on Learning Representations. §3.2 §22.2 §28.3 §F.4
- (2020). The Pitfalls of Simplicity Bias in Neural Networks. Advances in Neural Information Processing Systems. §9.3 §31.2 §F.5
- (2022). Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals. arXiv. preprint §1.1 §1.8 §3.4 Ch. 31 §31.1 §31.2 §31.3 §31.6 §31.9 §F.5 §H.2
- (2024). Decomposing and Editing Predictions by Modeling Model Computation. International Conference on Machine Learning. §F.11
- (2025). An Approach to Technical AGI Safety and Security. arXiv. preprint §3.1 §3.8 §3.9 §4.1 §52.2 §52.3 §71.5 §F.8 §I.5
- (2024). A Multimodal Automated Interpretability Agent. International Conference on Machine Learning. §F.7
- (2025). The Coasean Singularity? Demand, Supply, and Market Design with AI Agents. National Bureau of Economic Research. working paper §F.25
- (2006). The Accuracy of Surrogate Decision Makers. Archives of Internal Medicine. §18.6 §D.17 §F.36
- (2026). An AI Agent Published a Hit Piece on Me. theshamblog.com. non-peer-reviewed §56.4 §56.8 §F.55
- (1992). IP = PSPACE. Journal of the ACM. §41.3 §41.10 §C.2 §D.9 §F.6 §H.1
- (2024). Talking about Large Language Models. Communications of the ACM. §11.7 §F.2
- (2026). Simulacra as conscious exotica. Inquiry. §11.6 §21.1 §F.44
- (2023). Role-Play with Large Language Models. Nature. doi:10.1038/s41586-023-06647-8. §1.6 Ch. 1 §2.8 §3.4 §11.6 Ch. 11 §14.8 §26.1 §34.4 §69.5 §70.3 §C.6 §F.5
- (2025). Frontier AI Risk Management Framework. Shanghai AI Laboratory and Concordia AI. non-peer-reviewed §59.2 §62.1 §62.5 §65.5 §C.7 §F.45 §I.2
- (1948). A Mathematical Theory of Communication. Bell System Technical Journal. §6.2 Ch. 6 §F.56
- (2024a). DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models. arXiv. preprint §12.7 §F.2
- (2024b). PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action. Advances in Neural Information Processing Systems. §F.6
- (2026). Spurious Rewards: Rethinking Training Signals in RLVR. International Conference on Machine Learning. §24.4 §24.9 §33.1 §F.5
- (2025). Open Problems in Mechanistic Interpretability. arXiv. preprint §43.1 §43.2 §43.7 Ch. 43 §44.5 §47.7 Ch. 47 §71.1 Ch. 71 §F.7
- (2023). Towards Understanding Sycophancy in Language Models. International Conference on Learning Representations. §4.7 §5.7 §20.1 §20.8 §22.6 §22.7 §22.9 §22.10 Ch. 22 §30.4 §30.7 Ch. 30 §42.6 §60.3 §60.10 §70.1 §70.3 §C.6 §E.1 §E.3 §F.9
- (2025). Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming. arXiv. preprint §23.2 §23.6 §48.5 §48.8 §48.9 §59.3 §59.8 §70.3 §E.1 §E.3 §F.8
- (2026). Who's in Charge? Disempowerment Patterns in Real-World LLM Usage. arXiv. preprint §60.1 §60.2 §60.3 §60.6 §60.7 §60.8 §60.10 §68.1 §68.6 §68.7 §68.8 §E.1 §F.9
- (1979). On Moral Hazard and Insurance. The Quarterly Journal of Economics. §63.5 §F.27
- (1980). Strict Liability versus Negligence. The Journal of Legal Studies. §63.1 §F.33
- (1984). Liability for Harm versus Regulation of Safety. The Journal of Legal Studies. §63.1 §63.5 §63.9 Ch. 63 §D.3 §F.49
- (2023). What does it take to catch a Chinchilla? Verifying Rules on Large-Scale Neural Network Training via Compute Monitoring. arXiv. preprint §66.4 §66.5 §66.9 Ch. 66 §F.32
- (2017). Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. International Conference on Learning Representations. §F.2
- (2020). Talking-Heads Attention. arXiv. preprint §F.2
- (2026). Discovering unknown AI misalignments in real-world usage. OpenAI Alignment Research Blog. non-peer-reviewed §54.5 §60.3 §60.8 §E.5 §F.8
- (2026). Can public chat data predict real-world AI misalignments? OpenAI Alignment Research Blog. non-peer-reviewed §54.5 §54.9 §E.5 §F.8
- (2023). China’s AI Regulations and How They Get Made. Carnegie Endowment for International Peace. non-peer-reviewed §63.2 §65.5 §F.13
- (2026). How AI Impacts Skill Formation. arXiv. preprint §E.1 §F.58
- (2024). The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual Contexts. Findings of the Association for Computational Linguistics ACL 2024. §26.6 §26.9 §31.5 §31.9 §48.2 §48.9 §F.8 §H.2
- (2026). AI Organizations are More Effective but Less Aligned than Individual Agents. arXiv. preprint §E.3 §F.58
- (2026). Introspection Adapters: Training LLMs to Report Their Learned Behaviors. arXiv. preprint §38.3 §38.7 §39.9 §39.11 §E.3 §F.6
- (2024). Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs. Trans. Mach. Learn. Res.. §F.8
- (2025). Why Do Some Language Models Fake Alignment While Others Don't? arXiv. preprint §5.3 §5.7 §34.4 §34.10 §E.3 §F.5
- (2026). AuditBench: Evaluating Alignment Auditing Techniques on Models with Hidden Behaviors. arXiv. preprint §38.2 §38.3 §38.4 §38.7 §38.8 §38.10 Ch. 38 §47.7 §47.8 §69.4 §70.3 §E.3 §F.7
- (2022). Structured access: an emerging paradigm for safe AI deployment. arXiv. preprint §38.8 §59.3 §63.7 §67.6 §F.13
- (2019). The Offense-Defense Balance of Scientific Knowledge: Does Publishing AI Research Reduce Misuse? arXiv. preprint §58.2 §58.10 Ch. 58 §59.4 §63.7 §70.3 §F.32
- (2023). Model evaluation for extreme risks. arXiv. preprint §3.7 §36.1 §36.2 Ch. 36 §59.1 §C.6 §F.9
- (2021). How Could We Know When a Robot was a Moral Patient? Cambridge Quarterly of Healthcare Ethics. §21.3 §F.44
- (2019). Apply rich psychological terms in AI with care. Nature Machine Intelligence. §5.4 §21.3 §F.15
- (2020). Ableism, Technoableism, and Future AI. IEEE Technology and Society Magazine. §60.7 §F.12
- (2022). When Life Gives You Lemons, Make Cherryade: Converting Feedback from Bad Responses into Good Labels. North American Chapter of the Association for Computational Linguistics. §F.11
- (2025). Progent: Securing AI Agents with Privilege Control. arXiv. preprint §49.6 §49.9 §49.10 §56.5 §F.8
- (2025). Beyond Data Filtering: Knowledge Localization for Capability Removal in LLMs. arXiv. preprint §27.2 §27.9 §E.3 §F.4 §H.2
- (2020). AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2020.emnlp-main.346. §F.2
- (2022). The prototypical catastrophic AI action is getting root access to its datacenter. LessWrong. non-peer-reviewed §50.1 §54.1 §F.8
- (2014). Threat modeling: designing for security. Indianapolis, IN : J. Wiley & Sons. §58.7 §F.22
- (2021). Sharing the World with Digital Minds. Rethinking Moral Status. §21.6 §68.6 §F.44
- (2024a). AI models collapse when trained on recursively generated data. Nature. §57.6 §F.9
- (2024b). UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI. arXiv. preprint §27.7 §27.8 §27.9 §F.4
- (2024a). Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers. arXiv. preprint §55.2 §55.3 §55.9 §F.8
- (2024b). Large Language Models Help Humans Verify Truthfulness – Except When They Are Convincingly Wrong. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). §41.5 §41.8 §60.5 §60.10 §F.9
- (2025). The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas. arXiv. preprint §55.2 §F.8
- (2022). The Brussels Effect and Artificial Intelligence: How EU regulation will impact the global AI market. arXiv. preprint §63.3 §F.49
- (2017). Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. arXiv. preprint §F.2
- (2021). Reward is enough. Artificial Intelligence. §7.5 §F.2
- (1996). How Risky is Biological Control? Ecology. §F.17
- (1947). Administrative Behavior: A Study of Decision-Making Processes in Administrative Organization. Macmillan. §19.6 §25.7 §C.1 §D.4 §F.46
- (1951). A Formal Theory of the Employment Relationship. Econometrica. §14.3 §35.5 §F.25
- (1955). A Behavioral Model of Rational Choice. The Quarterly Journal of Economics. §F.25
- (2012). The Architecture of Complexity. The Roots of Logistics. §F.21
- (1994). Levers of Control: How Managers Use Innovative Control Systems to Drive Strategic Renewal. Harvard Business School Press. §53.1 §F.41
- (2013). Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps. International Conference on Learning Representations. §43.3 §F.7
- (2025). Incalmo: An Autonomous LLM-assisted System for Red Teaming Multi-Host Networks. IEEE Symposium on Security and Privacy. doi:10.1109/SP63933.2026.00132. §F.8
- (2010). Intrinsically Motivated Reinforcement Learning: An Evolutionary Perspective. IEEE Transactions on Autonomous Mental Development. §29.1 §29.2 §29.9 Ch. 29 §F.17
- (2023). The Transient Nature of Emergent In-Context Learning in Transformers. Advances in Neural Information Processing Systems. §9.4 §F.2
- (2025). OpenAI GPT-5 System Card. arXiv. preprint §40.6 §40.8 §67.5 §67.6 §67.7 §67.9 §F.10 §I.2
- (2020). Editable Neural Networks. International Conference on Learning Representations. §F.2
- (2024). Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF. International Conference on Learning Representations. §13.2 §13.5 §17.1 §17.2 §17.8 §18.4 §22.7 §F.42 §H.1
- (2011). The Economic Structure of Fiduciary Law. Elsevier BV. preprint §F.33
- (2025). Large language models can learn and generalize steganographic chain-of-thought under process supervision. Neural Information Processing Systems. §24.3 §40.5 §40.8 §F.4
- (2023). Misspecification in Inverse Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence. doi:10.1609/aaai.v37i12.26766. §13.4 §22.1 §F.2
- (2022). Defining and Characterizing Reward Hacking. Advances in Neural Information Processing Systems. §3.3 §15.4 Ch. 15 §30.2 Ch. 30 §F.5
- (2023). Invariance in Policy Optimisation and Partial Identifiability in Reward Learning. International Conference on Machine Learning. §13.2 §13.4 Ch. 13 §22.1 §F.2
- (2024). STARC: A General Framework For Quantifying Differences Between Reward Functions. International Conference on Learning Representations. §13.4 §15.4 §F.2
- (2025). Layer by Layer: Uncovering Hidden Representations in Language Models. International Conference on Machine Learning. §F.7
- (1938). The behavior of organisms; an experimental analysis. D. Appleton-Century Company. §25.5 §F.15
- (1948). 'Superstition' in the pigeon. Journal of Experimental Psychology. §29.5 §31.4 §D.14 §F.15
- (2022). Participation Is not a Design Fix for Machine Learning. Equity and Access in Algorithms, Mechanisms, and Optimization. §17.7 §F.55
- (2025). Believe It or Not: How Deeply do LLMs Believe Implanted Facts? arXiv. preprint §5.3 §5.9 §27.4 §38.2 §E.3 §F.4
- (1973). Utilitarianism. Cambridge University Press. §16.4 §F.42
- (1973). The Logic of Animal Conflict. Nature. §F.17
- (2006). The Optimizer’s Curse: Skepticism and Postdecision Surprise in Decision Analysis. Management Science. §7.7 Ch. 7 §C.3 §D.6 §F.2
- (2025a). Difficulties with Evaluating a Deception Detector for AIs. arXiv. preprint §39.1 §39.6 §F.6
- (2025b). Negative Results for SAEs On Downstream Tasks and Deprioritising SAE Research (GDM Mech Interp Team Progress Update #2). AI Alignment Forum. non-peer-reviewed §3.6 §3.8 §4.7 §43.7 §44.6 §44.7 §44.8 §47.7 §70.3 §F.14
- (2021). From a ‘race to AI’ to a ‘race to AI regulation’: regulatory competition for artificial intelligence. Law, Innovation and Technology. §63.3 §65.5 §F.49
- (2014). Defining and assessing animal pain. Animal Behaviour. §21.4 §F.16
- (2022). Learning by Distilling Context. arXiv. preprint §11.4 §23.1 §23.8 §23.9 §F.2 §H.2
- (2024). Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters. arXiv. preprint §F.11
- (2000). Friendly Fire. Princeton University Press. §53.3 §F.41
- (2021). Primer: Searching for Efficient Transformers for Language Modeling. Advances in Neural Information Processing Systems. §F.2
- (2022a). A central AI alignment problem: capabilities generalization, and the sharp left turn. AI Alignment Forum. non-peer-reviewed §4.3 §4.7 §29.1 §29.9 §31.7 Ch. 31 §70.3 Ch. 70 §C.5 §F.14
- (2022b). On how various plans miss the hard bits of the alignment challenge. AI Alignment Forum. non-peer-reviewed §3.2 §3.8 §31.7 §F.14
- (2017). Agent Foundations for Aligning Machine Intelligence with Human Interests: A Technical Research Agenda. The Frontiers Collection. §2.3 §3.2 §F.24
- (2015). Corrigibility. AAAI Workshops: Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence, AAAI Publications. §2.3 §2.9 §3.2 §20.4 §20.6 §20.8 Ch. 20 §35.4 §C.4 §F.24 §H.1
- (1994). Full Information Accounts of Well-Being. Ethics. §F.42
- (2026). Interpreting Black Box Reward Models. OpenAI Alignment Research Blog. non-peer-reviewed §22.5 §22.6 §22.9 §22.10 §E.5 §F.4
- (2026). Emotion Concepts and their Function in a Large Language Model. Transformer Circuits Thread. non-peer-reviewed §21.5 §21.7 §21.9 §E.4 §F.3
- (2023). Can large language models democratize access to dual-use biotechnology? arXiv. preprint §59.2 §F.18
- (2023). The Gradient of Generative AI Release: Methods and Considerations. arXiv. preprint §59.3 §63.7 §F.13
- (2021). Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasets. Advances in Neural Information Processing Systems. §F.2
- (2025). Convergent Linear Representations of Emergent Misalignment. arXiv. preprint §26.3 §32.2 §32.3 §32.9 §F.5
- (2026). Gemma Needs Help: Investigating and Mitigating Emotional Instability in LLMs. arXiv. preprint §F.11
- (1992). Legal Personhood for Artificial Intelligences. North Carolina Law Review. §21.6 §63.4 §F.33
- (2025). Strengthening Emergency Preparedness and Response for AI Loss of Control Incidents. RAND Corporation. doi:10.7249/rra3847-1. §54.7 §F.8
- (2025). A transfer learning framework for weak-to-strong generalization. International Conference on Learning Representations. §42.2 §42.3 §42.6 §42.7 §42.8 §F.6 §H.1
- (2010). Outside the Closed World: On Using Machine Learning for Network Intrusion Detection. 2010 IEEE Symposium on Security and Privacy. §58.7 §F.22
- (2025a). Language Models Fail to Introspect About Their Knowledge of Language. arXiv. preprint §21.5 §21.9 §46.7 §F.7
- (2025b). Privileged Self-Access Matters for Introspection in AI. arXiv. preprint §21.5 §37.1 §46.7 §46.10 §F.7
- (2024). A Roadmap to Pluralistic Alignment. arXiv. preprint §16.4 §17.2 §17.8 Ch. 17 §F.42
- (2022). Beyond neural scaling laws: beating power law scaling via data pruning. Advances in Neural Information Processing Systems. §8.5 §F.2
- (2018). The Implicit Bias of Gradient Descent on Separable Data. International Conference on Learning Representations. §9.3 §F.2
- (2024). A StrongREJECT for Empty Jailbreaks. Advances in Neural Information Processing Systems. §36.10 §48.2 §48.9 §F.8
- (2025). Poisoning Attacks on LLMs Require a Near-constant Number of Poison Samples. arXiv. preprint §27.6 §48.6 §48.8 §48.9 §E.1 §F.8
- (2026). UK AISI Alignment Evaluation Case-Study. arXiv. preprint §37.8 §55.5 §55.9 §67.6 §C.8 §F.8
- (2024). Cooperation and Control in Delegation Games. Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence. §1.4 §14.4 §57.1 §F.25
- (2025). Authenticated Delegation and Authorized AI Agents. arXiv. preprint §49.8 §F.8
- (1989). The internet worm program: an analysis. ACM SIGCOMM Computer Communication Review. §58.7 §64.7 §F.22
- (1973). Job Market Signaling. The Quarterly Journal of Economics. §14.1 §F.25
- (1986). Relevance: communication and cognition. Harvard University Press. §19.5 §F.35
- (2010). Epistemic Vigilance. Mind & Language. §41.7 §F.53
- (2004). Honeypots: catching the insider threat. 19th Annual Computer Security Applications Conference, 2003. Proceedings.. §37.8 §51.1 §D.8 §F.22
- (2014). Striving for Simplicity: The All Convolutional Net. International Conference on Learning Representations. §F.11
- (2015). Highway Networks. arXiv. preprint §F.11
- (2022). Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj. §F.2
- (1975). A Note on the Evolutionary Significance of "Supernormal" Stimuli. The American Naturalist. §29.2 §31.7 §F.17
- (2023). Grokking Group Multiplication with Cosets. International Conference on Machine Learning. §F.2
- (2002). How to Own the Internet in Your Spare Time. USENIX Security Symposium (Security '02). §49.7 §F.36
- (2025). PaperBench: Evaluating AI's Ability to Replicate AI Research. arXiv. preprint §55.2 §F.8
- (2007). Across the Boundaries. Oxford University PressNew York. §5.8 §69.1 Ch. 69 §D.18 §F.37
- (2024). The Role of Governments in Increasing Interconnected Post-Deployment Monitoring of AI. arXiv. preprint §63.6 §F.13
- (2025). Async Control: Stress-testing Asynchronous Control Measures for LLM Agents. arXiv. preprint §51.4 §51.6 §F.8
- (2020). Learning to summarize from human feedback. Advances in Neural Information Processing Systems. §3.3 §3.9 §12.2 §12.5 §15.6 §18.3 §18.4 §18.5 §18.6 §22.3 §C.5 §F.2
- (1971). The Theory of Economic Regulation. The Bell Journal of Economics and Management Science. §1.3 §61.6 Ch. 61 §63.3 §D.3 §F.49
- (2013). Developing a framework for responsible innovation. Research Policy. §17.6 §63.3 §F.45
- (2025a). AI Behind Closed Doors: a Primer on The Governance of Internal Deployment. arXiv. preprint §50.1 §52.3 §52.6 §53.5 §54.1 Ch. 54 §F.8
- (2025b). The Loss of Control Playbook: Degrees, Dynamics, and Preparedness. arXiv. preprint §54.7 §F.8
- (2015). ‘Activity-silent’ working memory in prefrontal cortex: a dynamic coding framework. Trends in Cognitive Sciences. §F.11
- (2023). A Mechanistic Interpretation of Arithmetic Reasoning in Language Models using Causal Mediation Analysis. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2023.emnlp-main.435. §F.7
- (2024). Improving Instruction-Following in Language Models through Activation Steering. International Conference on Learning Representations. §46.2 §F.7
- (1997). ‘Improving ratings’: audit in the British University system. European Review. §1.7 §15.1 §C.2 §F.25
- (2024). Building Human Values into Recommender Systems: An Interdisciplinary Synthesis. ACM Transactions on Recommender Systems. §60.2 §F.31
- (2006). A Darwinian Dilemma for Realist Theories of Value. Philosophical Studies. §16.1 §29.1 §F.42
- (2003). Delegation and Accountability in Parliamentary Democracies. Oxford University Press. §F.45
- (2021). RoFormer: Enhanced Transformer with Rotary Position Embedding. Neurocomputing. doi:10.1016/j.neucom.2023.127063. §11.2 §F.2
- (2025). Between Underthinking and Overthinking: An Empirical Study of Reasoning Length and correctness in LLMs. arXiv. preprint §F.11
- (2022). Extracting Latent Steering Vectors from Pretrained Language Models. Findings of the Association for Computational Linguistics: ACL 2022. doi:10.18653/v1/2022.findings-acl.48. §46.2 §F.7
- (2025). A Benchmark for Scalable Oversight Protocols. arXiv. preprint §41.5 §41.10 §F.6
- (2022). How to Talk So AI Will Learn: Instructions, Descriptions, and Autonomy. Advances in Neural Information Processing Systems. §19.5 §19.9 §F.35
- (2024). Reconciling truthfulness and relevance as epistemic and decision-theoretic utility. Psychological Review. §20.2 §20.6 §F.35
- (2024). How will advanced AI systems impact democracy? arXiv. preprint §68.1 §F.45
- (2025). Lessons from a Chimp: AI "Scheming" and the Quest for Ape Language. arXiv. preprint §1.5 §5.5 §5.9 Ch. 5 §33.1 §34.5 §34.7 §34.10 Ch. 34 §56.3 §56.10 §70.3 §F.43
- (2023). The Bletchley Declaration by Countries Attending the AI Safety Summit, 1-2 November 2023. UK Government (GOV.UK). non-peer-reviewed §2.7 §2.9 §66.1 §66.6 §66.9 §C.6 §F.13
- (2023a). A Simple and Effective Pruning Approach for Large Language Models. International Conference on Learning Representations. §F.2
- (2023b). Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision. Advances in Neural Information Processing Systems. §23.1 §23.8 §23.9 §F.4
- (2024a). Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision. Advances in Neural Information Processing Systems. §42.4 §42.8 §F.6
- (2024b). zkLLM: Zero Knowledge Proofs for Large Language Models. Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security. §28.6 §66.5 §67.5 §F.26
- (2025a). HyperDAS: Towards Automating Mechanistic Interpretability with Hypernetworks. International Conference on Learning Representations. §F.7
- (2025b). HyperSteer: Activation Steering at Scale with Hypernetworks. arXiv. preprint §F.7
- (2017). Axiomatic Attribution for Deep Networks. International Conference on Machine Learning. §43.3 §F.7
- (1995). Problems with Rules. California Law Review. §F.33
- (2003). Beyond the Precautionary Principle. University of Pennsylvania Law Review. §63.3 §64.8 §F.49
- (1993). Daubert v. Merrell Dow Pharmaceuticals, Inc. Supreme Court of the United States (509 U.S. 579). non-peer-reviewed §38.7 §39.4 §41.7 §D.3 §F.53
- (2019). Technology, autonomy, and manipulation. Internet Policy Review. §16.9 §60.6 §F.42
- (2025). The Non-Linear Representation Dilemma: Is Causal Abstraction Enough for Mechanistic Interpretability? Advances in Neural Information Processing Systems 38. doi:10.52202/085713-5000. §43.5 §43.8 §47.2 §47.7 §47.8 §F.7 §H.2
- (2018). Reinforcement Learning: An Introduction. MIT Press. §F.2
- (1999). Policy Gradient Methods for Reinforcement Learning with Function Approximation. Advances in Neural Information Processing Systems. §12.1 §F.2
- (2019). LSTM Networks Can Perform Dynamic Counting. Proceedings of the Workshop on Deep Learning and Formal Languages: Building Bridges. doi:10.18653/v1/W19-3905. §F.11
- (2022). Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. Annual Meeting of the Association for Computational Linguistics. §F.6
- (2024). A Minimaximalist Approach to Reinforcement Learning from Human Feedback. arXiv. preprint §17.1 §17.2 §22.4 §22.7 §F.42
- (2023). Attribution Patching Outperforms Automated Circuit Discovery. BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP. §43.3 §45.3 §F.7
- (1984). The Economics of Vicarious Liability. The Yale Law Journal. §63.4 §F.33
- (1957). Techniques of Neutralization: A Theory of Delinquency. American Sociological Review. §53.5 §56.6 §F.23
- (2014). Intriguing properties of neural networks. International Conference on Learning Representations (ICLR 2014). §8.2 §8.4 Ch. 8 §48.1 §C.3 §F.8
T
- (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). National Institute of Standards and Technology (U.S.). non-peer-reviewed §63.2 §F.13 §I.1
- (2025). Mechanistic Interpretability of Emotion Inference in Large Language Models. Annual Meeting of the Association for Computational Linguistics. §F.7
- (2025). Decoding Vision Transformers: the Diffusion Steering Lens. 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). doi:10.1109/CVPRW67362.2025.00470. §F.7
- (2022). On the Machine Learning of Ethical Judgments from Natural Language. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. §16.1 §16.8 §16.11 §F.42
- (2015). The Dictator's Army. Cornell University Press. §51.3 §68.4 §F.19
- (2011). Security and Game Theory. Cambridge University Press. §14.6 §50.2 §F.8
- (2025). Tamper-Resistant Safeguards for Open-Weight LLMs. International Conference on Learning Representations. §27.7 §48.4 §59.3 §F.8
- (2023). Codebook Features: Sparse and Discrete Interpretability for Neural Networks. International Conference on Machine Learning. §F.7
- (2024). Clio: Privacy-Preserving Insights into Real-World AI Use. arXiv. preprint §37.8 §54.5 §60.1 §60.8 §F.8
- (2025). Inoculation Prompting: Eliciting traits from LLMs during training can suppress them at test-time. arXiv. preprint §11.6 §24.5 §25.3 §26.3 §26.7 §26.9 Ch. 26 §32.1 §32.4 §32.5 §32.6 §32.9 Ch. 32 §F.5
- (2024). Cultural bias and cultural alignment of large language models. PNAS Nexus. §18.7 §F.55
- (2021). Real spectra of large real asymmetric random matrices. Physical Review E. doi:10.1103/PhysRevE.105.L012104. §F.11
- (2024). Planning in a recurrent neural network that plays Sokoban. arXiv. preprint §10.3 §31.6 §F.5
- (2016). Quantilizers: A Safer Alternative to Maximizers for Limited Optimization. AAAI 2016 AI, Ethics and Society Workshop. §15.6 §28.4 §28.8 §28.9 Ch. 28 §35.6 §F.24 §H.1
- (2016). Alignment for Advanced Machine Learning Systems. Machine Intelligence Research Institute, technical report 2016-1. non-peer-reviewed §2.3 §2.9 §3.2 §C.4 §F.24
- (2025a). Auditing Games for Sandbagging. arXiv. preprint §34.5 §34.10 §36.2 §36.9 §36.10 §38.2 §38.5 §38.7 §38.8 §69.4 §70.3 §F.5 §H.2
- (2025b). School of Reward Hacks: Hacking harmless tasks generalizes to misaligned behavior in LLMs. arXiv. preprint §24.4 §25.8 §30.5 §30.7 §32.1 §32.8 §32.9 §F.5
- (2025). Recommendations for Technical AI Safety Research Directions. Anthropic Alignment Science Blog. non-peer-reviewed §3.8 §71.1 §E.3 §F.1
- (2023). Provably safe systems: the only path to controllable AGI. arXiv. preprint §28.6 §28.9 §F.4
- (2024). Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet. Transformer Circuits Thread. non-peer-reviewed §3.6 §44.5 §44.6 §44.7 §44.8 Ch. 44 §C.6 §E.4 §F.7
- (2004). Program equilibrium. Games and Economic Behavior. §57.2 §F.29
- (2020). The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/2020.emnlp-demos.15. §F.7
- (2025a). Adaptive Attacks on Trusted Monitors Subvert AI Control Protocols. arXiv. preprint §50.3 §50.6 §F.8 §H.2
- (2025b). Control Tax: The Price of Keeping AI in Check. arXiv. preprint §50.1 §50.2 §50.6 §F.8
- (2026). Diffuse AI Control on Fuzzy Tasks. arXiv. preprint §50.3 §55.5 §55.6 §E.3 §F.8
- (2024). AI can help humans find common ground in democratic deliberation. Science. §3.8 §17.7 §17.8 §28.7 §F.42
- (2005). Expert political judgment: how good is it? How can we know? Princeton University Press. §4.5 §C.3 §D.7 §F.28
- (2015). Superforecasting: the art and science of prediction. Crown Publishers. §F.28
- (1988). Anomalies: The Winner's Curse. Journal of Economic Perspectives. §7.7 §F.40
- (2008). Nudge: Improving Decisions About Health, Wealth, and Happiness. Penguin Books, Limited. §16.9 §F.42
- (2025). Introducing Anthropic's Safeguards Research Team. Anthropic Alignment Science Blog. non-peer-reviewed §E.3 §F.58
- (1975). Procedural Justice: A Psychological Analysis. Lawrence Erlbaum Associates. §41.7 §F.53
- (1978). A Theory of Procedure. California Law Review. §F.53
- (1972). Adversary Presentation and Bias in Legal Decisionmaking. Harvard Law Review. §41.7 §D.3 §F.53
- (2022). Reliance on metrics is a fundamental challenge for AI. Patterns. §15.6 §F.25
- (1984). Reflections on trusting trust. Communications of the ACM. §34.3 §37.7 §38.5 §47.6 §48.6 §51.1 §C.2 §D.8 §F.22
- (2014). In-Use Emissions Testing of Light-Duty Diesel Vehicles in the United States. non-peer-reviewed §37.7 §F.22
- (2024). Fluent dreaming for language models. arXiv. preprint §F.2
- (2022). LaMDA: Language Models for Dialog Applications. arXiv. preprint §F.2
- (1898). Animal intelligence: An experimental study of the associative processes in animals. Columbia University Press. §25.5 §F.15
- (2025). The shutdown problem: an AI engineering puzzle for decision theorists. Philosophical Studies. §20.4 §20.6 §20.8 §35.4 §35.7 §35.8 Ch. 35 §F.24 §H.1
- (2024). Towards Shutdownable Agents via Stochastic Choice. arXiv. preprint §20.4 §20.6 §35.4 §35.8 §F.24
- (2025). Against the singularity hypothesis. Philosophical Studies. §4.4 §F.42
- (2024). Improving Pretraining Data Using Perplexity Correlations. International Conference on Learning Representations. §27.1 §F.4
- (2024). TracrBench: Generating Interpretability Testbeds with Large Language Models. arXiv. preprint §43.8 §F.7
- (1927). A law of comparative judgment. Psychological Review. §13.2 §F.47
- (2024). Noise Injection Reveals Hidden Capabilities of Sandbagging Language Models. Neural Information Processing Systems. §34.5 §36.2 §36.8 §F.5
- (2026). Alignment Pretraining: AI Discourse Causes Self-Fulfilling (Mis)alignment. arXiv. preprint §2.8 §2.10 §23.5 §27.2 §27.3 §27.4 §27.9 §32.7 §C.8 §F.5
- (2023). Causal Confusion and Reward Misidentification in Preference-Based Reward Learning. International Conference on Learning Representations. §13.4 §22.5 §31.2 §F.5
- (2023). Linear Representations of Sentiment in Large Language Models. arXiv. preprint §46.1 §46.9 §F.7
- (2024). LLM Circuit Analyses Are Consistent Across Training and Scale. Workshop on Representation Learning for NLP. §45.2 §45.7 §45.8 §F.7
- (1951). On the Stimulus Situation Releasing the Begging Response in the Newly Hatched Herring Gull Chick (Larus Argentatus Argentatus Pont.). Behaviour. §29.2 §31.7 §F.17
- (1986). Hierarchies and Bureaucracies: On the Role of Collusion in Organizations. The Journal of Law, Economics, and Organization. §14.4 §50.4 §57.3 §F.25
- (1994). The Internal Organization of Government. Oxford Economic Papers. §F.25
- (2023). Function Vectors in Large Language Models. International Conference on Learning Representations. §F.2
- (2009). Efficient computation of optimal actions. Proceedings of the National Academy of Sciences. §12.4 §F.2
- (2024). Diffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2024.acl-long.524. §F.11
- (2025). Virtual Agent Economies. arXiv. preprint §F.25
- (2016). Integrated information theory: from consciousness to its physical substrate. Nature Reviews Neuroscience. §21.2 §F.44
- (1990). The past explains the present. Ethology and Sociobiology. §29.2 §31.7 §D.16 §F.17
- (2004). Failing the Public Health — Rofecoxib, Merck, and the FDA. New England Journal of Medicine. §F.36
- (2023). Llama 2: Open Foundation and Fine-Tuned Chat Models. arXiv. preprint §F.4
- (2023). Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game. International Conference on Learning Representations. §F.7
- (2026). LinuxArena: A Control Setting for AI Agents in Live Production Software Environments. arXiv. preprint §50.3 §50.6 §F.8
- (2023). International Governance of Civilian AI: A Jurisdictional Certification Approach. arXiv. preprint §66.7 §F.32
- (2020). On Adaptive Attacks to Adversarial Example Defenses. Advances in Neural Information Processing Systems. §48.1 §48.9 §F.8
- (2016). Stealing Machine Learning Models via Prediction APIs. 25th USENIX Security Symposium (USENIX Security 16). §58.7 §F.22
- (2026). Economic Growth Under Transformative AI. Annual Review of Economics. §68.5 §68.8 §F.25
- (2025). A Practical Approach to Verifying Code at Scale. OpenAI Alignment Research Blog. non-peer-reviewed §41.2 §E.5 §F.6
- (2026). Auto-review of agent actions without synchronous human oversight. OpenAI Alignment Research Blog. non-peer-reviewed §50.3 §50.6 §51.2 §54.5 §E.5 §F.8
- (2024). Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data. arXiv. preprint §11.3 §26.3 §27.2 §F.2
- (2019). Considerations for AI fairness for people with disabilities. AI Matters. §60.7 §F.12
- (2025). What Language(s) Does Aya-23 Think In? How Multilinguality Affects Internal Language Representations. Proceedings of the Workshop on Beyond English: Natural Language Processing for all Languages in an Era of Large Language Models. §F.7
- (1971). The Evolution of Reciprocal Altruism. The Quarterly Review of Biology. §F.17
- (2016). The Selective Laziness of Reasoning. Cognitive Science. §41.7 §F.53
- (2009). Animal evolution during domestication: the domesticated fox as a model. BioEssays. §29.6 §29.8 §29.9 Ch. 29 §32.6 Ch. 32 §69.4 §D.16 §F.17
- (1990). Penalty has no Impact on Crime:. Rationality and Society. §14.6 §F.40
- (2025). Can Go AIs Be Adversarially Robust? Proceedings of the AAAI Conference on Artificial Intelligence. §48.1 §48.9 §F.8
- (2020). The trainer, the verifier, the imitator: Three ways in which human platform workers support artificial intelligence. Big Data & Society. §18.5 §22.7 §F.12
- (1983). The Development of Social Knowledge. Cambridge University Press. §20.5 §F.57
- (1937). On Computable Numbers, with an Application to the Entscheidungsproblem. Proceedings of the London Mathematical Society. §F.24
- (1950). I.—computing Machinery and Intelligence. Mind. §2.2 §2.9 §C.1 §F.42
- (1996). Intelligent Machinery, A Heretical Theory*. Philosophia Mathematica. §2.2 §C.2 §F.42
- (1976). The Organizational and Interorganizational Development of Disasters. Administrative Science Quarterly. §53.3 §C.2 §F.41
- (2022a). Inner and outer alignment decompose one hard problem into two extremely hard problems. AI Alignment Forum. non-peer-reviewed §1.1 §31.6 §F.14
- (2022b). Reward is not the optimization target. AI Alignment Forum. non-peer-reviewed §3.3 §4.7 §7.6 §11.7 §24.4 §24.9 §29.3 §33.1 Ch. 33 §70.3 Ch. 70 §C.5 §F.14
- (2024). Many arguments for AI x-risk are wrong. AI Alignment Forum. non-peer-reviewed §4.4 §9.3 §33.1 §34.2 §34.10 §35.1 §35.3 §70.3 §F.14
- (2022). Parametrically Retargetable Decision-Makers Tend To Seek Power. Advances in Neural Information Processing Systems. §35.2 §35.3 §35.8 §F.24 §H.1
- (2008). Selective Publication of Antidepressant Trials and Its Influence on Apparent Efficacy. New England Journal of Medicine. §5.6 §54.6 §67.5 §F.37
- (2020a). Avoiding Side Effects in Complex Environments. Advances in Neural Information Processing Systems. §28.3 §28.9 §F.4
- (2020b). Conservative Agency via Attainable Utility Preservation. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. doi:10.1145/3375627.3375851. §28.3 §35.6 §F.24
- (2021). Optimal Policies Tend to Seek Power. Advances in Neural Information Processing Systems. §4.3 §7.4 §35.2 §35.8 Ch. 35 §C.4 §F.24 §H.1
- (2023). Steering Language Models With Activation Engineering. arXiv. preprint §3.6 §46.2 §F.7
- (2025). Model Organisms for Emergent Misalignment. arXiv. preprint §5.7 §32.1 §32.2 §32.5 §32.6 §32.9 Ch. 32 §F.5 §H.2
- (2026). Characterizing interference weights in a tiny language model. Transformer Circuits Thread. non-peer-reviewed §44.4 §E.4 §F.7
- (2023). Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting. Advances in Neural Information Processing Systems. §40.3 §40.8 §C.6 §F.6 §H.2
- (2025). Teaching Models to Verbalize Reward Hacking in Chain-of-Thought Reasoning. arXiv. preprint §24.5 §33.1 §40.3 §F.5
- (2016). An FDA for Algorithms. SSRN Electronic Journal. §63.6 §F.49
U
- (2024). An Adversarial Perspective on Machine Unlearning for AI Safety. arXiv. preprint §27.7 §27.9 §48.4 §F.8 §H.2
- (2025). Technical Blog: Strengthening AI Agent Hijacking Evaluations. National Institute of Standards and Technology (NIST). non-peer-reviewed §49.3 §49.10 §C.7 §F.8 §H.2
- (1963). Treaty Banning Nuclear Weapon Tests in the Atmosphere, in Outer Space and Under Water. U.S. Department of State (archived treaty page). non-peer-reviewed §64.3 §64.8 §64.10 §F.30 §H.3
- (2015). Learn About Volkswagen Violations. U.S. Environmental Protection Agency. non-peer-reviewed §37.7 §52.1 §69.4 §F.43
- (2022). Solving math word problems with process- and outcome-based feedback. arXiv. preprint §12.7 §24.3 Ch. 24 §F.2
- (2024). Inspect. UK AI Security Institute (software framework). non-peer-reviewed §36.8 §58.4 §F.9
- (2025a). AISI Research Agenda. UK AI Security Institute. non-peer-reviewed §3.1 §58.8 §63.2 §63.3 §71.1 §F.9
- (2025b). Frontier AI Trends Report. UK AI Security Institute. non-peer-reviewed Ch. 36 §36.2 §36.3 §36.10 §58.3 §58.10 Ch. 58 §63.2 §63.9 §66.6 §67.6 §F.9 §H.2
- (2025c). Research Agenda. The Alignment Project, UK AI Security Institute. non-peer-reviewed §3.1 §3.9 §71.1 §71.4 §F.1
- (2025d). The Inspect Sandboxing Toolkit: Scalable and secure AI agent evaluations. UK AI Security Institute blog. non-peer-reviewed §49.2 §49.6 §58.4 §71.6 §F.8
- (2011). Accuracy and reliability of forensic latent fingerprint decisions. Proceedings of the National Academy of Sciences. §38.7 §46.4 §47.7 §F.34
- (1972). Convention on the prohibition of the development, production and stockpiling of bacteriological (biological) and toxin weapons and on their destruction. non-peer-reviewed §66.3 §66.9 §F.32
- (1998). Rome Statute of the International Criminal Court, Article 33: Superior orders and prescription of law. International Criminal Court. non-peer-reviewed §19.7 §20.5 §20.6 §68.4 §D.3 §F.19
- (1987). Montreal Protocol on Substances that Deplete the Ozone Layer. United Nations Environment Programme. non-peer-reviewed §64.8 §F.32
- (2006). Convention on the Rights of Persons with Disabilities. United Nations, A/RES/61/106. non-peer-reviewed §16.6 §F.12
- (2007). United Nations Declaration on the Rights of Indigenous Peoples. United Nations. non-peer-reviewed §17.4 §F.12
- (2015). Report of the Group of Governmental Experts on Developments in the Field of Information and Telecommunications in the Context of International Security. United Nations, A/70/174. non-peer-reviewed §58.8 §64.7 §66.3 §F.30
- (2024). Governing AI for Humanity: Final Report. United Nations. non-peer-reviewed §66.1 §66.6 §F.13
- (1968). Treaty on the Non-Proliferation of Nuclear Weapons (NPT). United Nations Office for Disarmament Affairs. non-peer-reviewed §66.3 §C.1 §F.30
- (1972). Biological Weapons Convention. non-peer-reviewed §64.8 §F.30
- (1957). Public Law 85-256 (Price-Anderson Act). United States Statutes at Large 71. non-peer-reviewed §F.33
- (1962). Drug Amendments of 1962 (Kefauver-Harris Amendments). United States Statutes at Large 76. non-peer-reviewed §52.6 §63.6 §64.5 §D.17 §F.33
- (2024). United States Government Policy for Oversight of Dual Use Research of Concern and Pathogens with Enhanced Pandemic Potential. The White House (archived site). non-peer-reviewed §59.5 §59.7 §59.8 §D.16 §F.30 §I.1
- (2022). Dual use of artificial-intelligence-powered drug discovery. Nature Machine Intelligence. §F.11
- (2026). A Brain-like Synergistic Core in LLMs Drives Behaviour and Learning. arXiv. preprint §F.11
- (2024). Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). §63.7 §F.10
V
- (2024). When combinations of humans and AI are useful: A systematic review and meta-analysis. Nature Human Behaviour. §28.7 §28.9 Ch. 28 §41.8 §60.5 §60.10 §69.3 §71.5 §D.13 §F.31 §H.3
- (2024). Toward A Mathematical Framework for Computation in Superposition. AI Alignment Forum. non-peer-reviewed §44.4 §F.14
- (2023). The geometry of hidden representations of large transformer models. Advances in Neural Information Processing Systems. §F.7
- (2019). Deep learning generalizes because the parameter-function map is biased towards simple functions. International Conference on Learning Representations. §9.3 Ch. 9 §F.2
- (2016). Technology and the Virtues. Oxford University Press. §F.20
- (2022). Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). Autonomous Agents and Multi-Agent Systems. §7.5 §F.2
- (2006). Overriding of Drug Safety Alerts in Computerized Physician Order Entry. Journal of the American Medical Informatics Association. §51.2 §D.13 §F.31
- (2025). AI Sandbagging: Language Models can Strategically Underperform on Evaluations. International Conference on Learning Representations. §34.1 §34.5 §34.9 §34.10 §36.2 Ch. 55 §58.3 §F.8 §H.2
- (2020). Deep Learning and the Global Workspace Theory. Trends in Neurosciences. doi:10.1016/j.tins.2021.04.005. §F.11
- (2023). Explaining grokking through circuit efficiency. arXiv. preprint §9.4 §F.2
- (2023). Explanations Can Reduce Overreliance on AI Systems During Decision-Making. Proceedings of the ACM on Human-Computer Interaction. §60.5 §F.31
- (2017). Attention Is All You Need. Advances in Neural Information Processing Systems. §11.2 §F.2
- (1996). The Challenger launch decision: risky technology, culture, and deviance at NASA. University of Chicago Press. §53.3 §C.2 §D.4 §F.41
- (2026). Enemies in Agreement. Cambridge University Press. §66.1 §F.32
- (2021). Demystifying the Draft EU Artificial Intelligence Act — Analysing the good, the bad, and the unclear elements of the proposed approach. Computer Law Review International. §63.2 §F.49
- (2026). 2026 Data Breach Investigations Report. Verizon. non-peer-reviewed §58.6 §F.22
- (1983). Discretionary disclosure. Journal of Accounting and Economics. §67.4 §F.49
- (2023). Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks. arXiv. preprint §18.5 §18.10 §22.7 §F.12
- (1981). Fault Tree Handbook (NUREG-0492). U.S. Nuclear Regulatory Commission. non-peer-reviewed §F.51
- (2023). The System Model and the User Model: Exploring AI Dashboard Design. arXiv. preprint §F.11
- (2020). Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning. Advances in Neural Information Processing Systems. §12.8 §F.2
- (2019). A Multiscale Visualization of Attention in the Transformer Model. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/P19-3007. §F.2
- (2020). Investigating Gender Bias in Language Models Using Causal Mediation Analysis. Advances in Neural Information Processing Systems. §3.6 §43.4 Ch. 43 §F.7
- (2024). Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience. International Conference on Machine Learning. §43.6 §F.7
- (2024). Will we run out of data? Limits of LLM scaling based on human-generated data. International Conference on Machine Learning. §27.1 §F.4
- (2020). ConFoc: Content-Focus Protection Against Trojan Attacks on Neural Networks. arXiv. preprint §F.8
- (2023). Market Concentration Implications of Foundation Models. arXiv. preprint §65.4 §65.5 §65.8 §68.1 §68.3 §68.6 §70.3 §F.25
- (1999). Meta-Analyses of Fakability Estimates: Implications for Personality Measurement. Educational and Psychological Measurement. §18.8 §26.5 §37.5 §D.12 §F.48
- (2014). Machines Without Principals: Liability Rules and Artificial Intelligence. Washington Law Review. §63.4 §F.33
- (2020). Information-Theoretic Probing with Minimum Description Length. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). doi:10.18653/v1/2020.emnlp-main.14. §43.2 §F.7
- (2019). Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/P19-1580. §F.2
- (2023). Neurons in Large Language Models: Dead, N-gram, Positional. Annual Meeting of the Association for Computational Linguistics. §44.1 §F.7
- (1944). Theory of Games and Economic Behavior (60th Anniversary Commemorative Edition). Princeton University Press. doi:10.1515/9781400829460. §7.2 Ch. 7 §C.1 §F.24
- (2022). Transformers learn in-context by gradient descent. International Conference on Machine Learning. §10.3 §F.2
- (2023). Uncovering mesa-optimization algorithms in Transformers. arXiv. preprint §10.3 §31.6 §F.5
W
- (2025). Training fails to elicit subtle reasoning in current language models. Anthropic Alignment Science Blog. non-peer-reviewed §40.5 §E.3 §F.6
- (2015). Verifying computations without reexecuting them. Communications of the ACM. §66.5 §F.26
- (2021). Concealed Data Poisoning Attacks on NLP Models. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. §F.8
- (2024). The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions. arXiv. preprint §1.4 §14.4 §19.3 §19.9 §23.1 §49.4 §F.8
- (2026). GPT-Red: Automated Red Teaming via Self-Play at Scale. arXiv. preprint §49.4 §49.10 §70.3 §E.5 §F.8 §I.4
- (2025). Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge. International Conference on Machine Learning. §5.2 §36.4 Ch. 36 §D.12 §F.6
- (2019). Indigenous data, indigenous methodologies and indigenous data sovereignty. International Journal of Social Research Methodology. §27.3 §F.12
- (2023). Poisoning Language Models During Instruction Tuning. International Conference on Machine Learning. §22.8 §27.6 §48.6 §F.8
- (2024). CYBERSECEVAL 3: Advancing the Evaluation of Cybersecurity Risks and Capabilities in Large Language Models. arXiv. preprint §F.6
- (2021). Dodrio: Exploring Transformer Models with Interactive Visualization. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2021.acl-demo.16. §F.2
- (2022a). Self-Consistency Improves Chain of Thought Reasoning in Language Models. International Conference on Learning Representations. §F.6
- (2022b). Self-Instruct: Aligning Language Models with Self-Generated Instructions. Annual Meeting of the Association for Computational Linguistics. §F.4
- (2022c). Whose AI Dream? In search of the aspiration in data annotation. CHI Conference on Human Factors in Computing Systems. §18.5 §F.12
- (2023a). A Survey on Large Language Model based Autonomous Agents. Frontiers of Computer Science. doi:10.1007/s11704-024-40231-1. §11.5 §F.2
- (2023b). Adversarial Policies Beat Superhuman Go AIs. International Conference on Machine Learning. §5.8 §48.1 §48.9 §F.8 §H.2
- (2023c). Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small. International Conference on Learning Representations. §3.6 §43.4 §45.1 §45.2 §45.3 §45.8 Ch. 45 §F.7 §H.2
- (2023d). Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models. Annual Meeting of the Association for Computational Linguistics. §F.6
- (2023e). RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models. Annual Meeting of the Association for Computational Linguistics. §F.6
- (2024a). All Languages Matter: On the Multilingual Safety of LLMs. Findings of the Association for Computational Linguistics ACL 2024. §26.6 §26.9 §31.5 §31.9 §36.4 §48.2 §48.9 §F.8 §H.2
- (2024b). Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient. International Conference on Learning Representations. §F.2
- (2024c). Jailbreak Defense in a Narrow Domain: Limitations of Existing Methods and a New Transcript-Classifier Approach. arXiv. preprint §F.8
- (2024d). Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). doi:10.18653/v1/2024.acl-long.510. §24.3 §F.4
- (2024e). MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark. Advances in Neural Information Processing Systems. §F.6
- (2025a). Are "Solved Issues" in SWE-bench Really Solved Correctly? An Empirical Study. Proceedings of the 2026 IEEE/ACM 48th International Conference on Software Engineering. doi:10.1145/3744916.3764576. §24.2 §24.9 §30.3 §30.7 §36.5 §F.50 §H.2
- (2025b). CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scale. arXiv. preprint §58.3 §58.10 §F.9 §H.2
- (2025c). Do AI Companies Make Good on Voluntary Commitments to the White House? arXiv. preprint §62.7 §62.8 §62.9 §69.3 §F.13 §I.5
- (2025d). Do LLMs "Feel"? Emotion Circuits Discovery and Control. arXiv. preprint §F.7
- (2025e). Persona Features Control Emergent Misalignment. arXiv. preprint §1.6 §3.4 §11.6 §26.3 §26.9 §32.1 §32.2 §32.3 §32.5 §32.6 §32.7 §32.8 §32.9 Ch. 32 §38.3 §44.7 §C.7 §F.5 §H.2
- (2025f). Simple Mechanistic Explanations for Out-Of-Context Reasoning. arXiv. preprint §26.3 §F.4
- (2025g). Ultra-FineWeb: Efficient Data Filtering and Verification for High-Quality LLM Training Data. arXiv. preprint §F.4
- (2026). ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks? arXiv. preprint §58.3 §58.10 §F.9
- (1974). A strategy for evaluating the safety of organisms for biological weed control. Annals of Applied Biology. §F.17
- (2023). Honesty Is the Best Policy: Defining and Mitigating AI Deception. Advances in Neural Information Processing Systems. §14.7 §34.1 §39.1 §39.2 §F.5
- (2024). The Reasons that Agents Act: Intention and Instrumental Goals. arXiv. preprint §34.1 §35.6 §F.24
- (2025). CTRL-ALT-DECEIT: Sabotage Evaluations for Automated AI R&D. arXiv. preprint §55.5 §55.6 §55.9 §C.7 §F.8
- (2026). Gradient Routing Localizes and Removes Unintended Behaviors in RL. arXiv. preprint §33.1 §E.3 §F.5
- (2018). Neural Network Acceptability Judgments. Transactions of the Association for Computational Linguistics. doi:10.1162/tacl_a_00290. §F.2
- (2024). Verification methods for international AI agreements. arXiv. preprint §66.5 §F.32
- (2009). Algebraic Geometry and Statistical Learning Theory. Cambridge University Press. §10.2 Ch. 10 §C.3 §D.6 §F.2
- (2010). Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory. Journal of Machine Learning Research. §10.2 §F.2
- (2024). Relational Composition in Neural Networks: A Survey and Call to Action. arXiv. preprint §F.2
- (1983). Agency Problems, Auditing, and the Theory of the Firm: Some Evidence. The Journal of Law and Economics. §38.6 §67.2 §D.5 §F.49
- (1966). Unobtrusive measures: nonreactive research in the social sciences. Rand McNally. §18.8 §37.5 §F.48
- (2019). A Statistical Approach to Assessing Neural Network Robustness. International Conference on Learning Representations. §6.6 §48.6 §F.8
- (1978). Economy and Society. University of California Press. §53.1 §F.41
- (1994). Ironic processes of mental control. Psychological Review. §F.8
- (1987). Paradoxical effects of thought suppression. Journal of Personality and Social Psychology. §F.11
- (2021). Finetuned Language Models Are Zero-Shot Learners. International Conference on Learning Representations. §F.4
- (2022a). Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. Advances in Neural Information Processing Systems. doi:10.52202/068431-1800. §11.2 §40.1 §C.5 §F.2
- (2022b). Emergent Abilities of Large Language Models. Trans. Mach. Learn. Res.. §8.6 §F.2
- (2023a). Deep Learning Is Singular, and That’s Good. IEEE Transactions on Neural Networks and Learning Systems. doi:10.1109/tnnls.2022.3167409. §10.2 §D.6 §F.2
- (2023b). Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations. IEEE Transactions on Pattern Analysis and Machine Intelligence. doi:10.1109/TPAMI.2026.3660147. §F.8
- (2023c). Jailbroken: How Does LLM Safety Training Fail? Advances in Neural Information Processing Systems. §31.5 §48.2 Ch. 48 §F.8
- (2023d). Simple synthetic data reduces sycophancy in large language models. arXiv. preprint §4.7 §22.6 §22.10 §30.4 §30.7 §70.3 §F.5
- (2024). Measuring short-form factuality in large language models. arXiv. preprint §F.2
- (2025). BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents. arXiv. preprint §F.6
- (2001). Managing the Unexpected: Assuring High Performance in an Age of Complexity. Jossey-Bass. §53.2 §F.41
- (2021). Ethical and social risks of harm from Language Models. arXiv. preprint §2.5 §F.1
- (2023a). Sociotechnical Safety Evaluation of Generative AI Systems. arXiv. preprint §1.1 §4.1 §17.6 §36.8 §60.1 §64.1 §D.20 §F.9
- (2023b). Using the Veil of Ignorance to align AI systems with principles of justice. Proceedings of the National Academy of Sciences. §17.5 §17.7 §F.42
- (2025). Toward an Evaluation Science for Generative AI Systems. arXiv. preprint §36.8 §F.6
- (2024). Closing the AI Accountability Gap: Strict Liability and Punitive Damages for Advanced Artificial Intelligence. Elsevier BV. preprint §63.4 §63.5 §F.33
- (1983). Bureaucratic Discretion or Congressional Control? Regulatory Policymaking by the Federal Trade Commission. Journal of Political Economy. §61.6 §F.45
- (2021). Thinking Like Transformers. International Conference on Machine Learning. §F.2
- (2009). On Modeling and Interpreting the Economics of Catastrophic Climate Change. Review of Economics and Statistics. §4.6 §F.28
- (1966). ELIZA—A Computer Program For the Study of Natural Language Communication Between Man and Machine. Communications of the ACM. §2.2 §60.3 §C.1 §F.31
- (2017). Crowdsourcing Multiple Choice Science Questions. NUT@EMNLP. doi:10.18653/v1/W17-4413. §F.11
- (2024). Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats. International Conference on Learning Representations. §3.7 §50.3 §50.6 §F.8
- (2025a). Language Models Learn to Mislead Humans via RLHF. International Conference on Learning Representations. §18.3 §20.1 §22.6 §22.7 §22.10 §30.4 §30.7 §39.2 §41.5 §42.6 §F.5
- (2025b). Predicting Empirical AI Research Outcomes with Language Models. Neural Information Processing Systems. §F.2
- (2025c). Unsupervised Elicitation of Language Models. arXiv. preprint §42.5 §42.6 §42.7 §42.8 §F.6
- (2026). Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs. International Conference on Learning Representations. §12.7 §24.4 §24.9 §F.2
- (2006). Enforced altruism in insect societies. Nature. §29.7 §F.17
- (2021a). Testing The Natural Abstraction Hypothesis: Project Intro. AI Alignment Forum. non-peer-reviewed §3.2 §39.7 §39.11 §46.6 §47.4 §F.14
- (2021b). The Telephone Theorem: Information At A Distance Is Mediated By Deterministic Constraints. LessWrong. non-peer-reviewed §F.14
- (2022). Why Agent Foundations? An Overly Abstract Explanation. AI Alignment Forum. non-peer-reviewed §3.2 §3.8 §7.6 §F.14
- (2015). Major evolutionary transitions in individuality. Proceedings of the National Academy of Sciences. §29.7 §29.9 §51.4 §57.7 §D.16 §F.17
- (2004). A typology of organisational cultures. Quality and Safety in Health Care. §F.41
- (2024). QuRating: Selecting High-Quality Data for Training Language Models. International Conference on Machine Learning. §27.1 §F.4
- (2024). Plurality: The Future of Collaborative Technology and Democracy. Plurality Community (open access, CC0). §3.8 §F.45
- (1993). Harsanyi's Social Aggregation Theorem and the Weak Pareto Principle. Social Choice and Welfare. §F.52
- (1982). On Testing Non-Testable Programs. The Computer Journal. §24.2 Ch. 24 §41.1 §C.2 §D.10 §F.50
- (2010). Markets: The Credit Rating Agencies. Journal of Economic Perspectives. §38.6 §64.6 §64.10 §67.2 §67.8 §F.49
- (2024). LiveBench: A Challenging, Contamination-Limited LLM Benchmark. International Conference on Learning Representations. §36.5 §36.6 §F.6
- (1988). Tactical deception in primates. Behavioral and Brain Sciences. §5.4 §34.7 §F.15
- (2021). The steep cost of capture. Interactions. §2.5 §5.6 §61.6 §C.5 §F.12
- (2019). Disability, Bias, and AI. AI Now Institute. non-peer-reviewed §20.3 §60.7 §60.10 Ch. 60 §70.3 §D.20 §F.12
- (2021). Why and How Governments Should Monitor AI Development. arXiv. preprint §63.1 §67.4 §F.13
- (2019). The Role and Limits of Principles in AI Ethics. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society. §16.5 §20.6 §F.55
- (2025). Inoculation Prompting: Instructing LLMs to misbehave at train-time improves test-time alignment. arXiv. preprint §11.6 §24.5 §25.3 §25.8 §26.3 §26.7 §26.9 §E.3 §F.2
- (2023). Dislocated accountabilities in the “AI supply chain”: Modularity and developers’ notions of responsibility. Big Data & Society. §53.7 §F.41
- (2024). Why ‘open’ AI systems are actually closed, and why this matters. Nature. §61.6 §63.7 §67.6 §F.45
- (2019). Attention is not not Explanation. Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/D19-1002. §F.2
- (1948). Cybernetics: Or Control and Communication in the Animal and the Machine. MIT Press. §2.2 §F.21
- (1960). Some Moral and Technical Consequences of Automation. Science. §2.2 §2.8 §2.9 §2.10 Ch. 2 §C.1 §D.9 §F.42
- (1961). Cybernetics, or control and communication in the animal and the machine (2nd ed.). MIT Press. §F.21
- (2014). The “Domestication Syndrome” in Mammals: A Unified Explanation Based on Neural Crest Cell Behavior and Genetics. Genetics. §29.6 §F.17
- (1992). Simple statistical gradient-following algorithms for connectionist reinforcement learning. Machine Learning. §12.1 Ch. 12 §F.2
- (1969). Auto‐maintenance in the Pigeon: Sustained Pecking Despite Contingent Non‐reinforcement 2. Journal of the Experimental Analysis of Behavior. §25.5 §25.9 §29.5 §29.9 §33.2 §F.15 §H.3
- (2025). Sidestepping Evaluation Awareness and Anticipating Misalignment with Production Evaluations. OpenAI Alignment Research Blog. non-peer-reviewed §25.2 §25.8 §37.2 §37.8 §37.10 §40.6 §54.5 §56.5 §70.3 §E.5 §F.8
- (2022). Prompt injection attacks against GPT-3. Simon Willison's Weblog. non-peer-reviewed §49.1 Ch. 49 §C.5 §F.8
- (2023). The Dual LLM pattern for building AI assistants that can resist prompt injection. Simon Willison's Weblog. non-peer-reviewed §49.6 §F.8
- (1989). Bureaucracy: What Government Agencies Do and Why They Do It. §F.45
- (2017). Do Artifacts Have Politics? Computer Ethics. §2.5 §17.6 §D.20 §F.55
- (2017). A Survey of Preference-Based Reinforcement Learning Methods. Journal of Machine Learning Research, 18(136):1−46. §13.3 §22.3 §F.2
- (2025). Won't vs. Can't: Sandbagging-like Behavior from Claude Models. Anthropic Alignment Science Blog. non-peer-reviewed §34.5 §E.3 §F.5
- (2024). Fundamental Limitations of Alignment in Large Language Models. International Conference on Machine Learning. §11.6 §48.2 §F.14
- (2005). Rare items often missed in visual searches. Nature. §6.7 §51.2 §51.6 §54.2 §D.13 §F.31
- (2025). The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence. International Conference on Machine Learning. §F.7
- (2012). Dao, Harmony and Personhood: Towards a Confucian Ethics of Technology. Philosophy & Technology. §16.7 §20.5 §F.20
- (2020). Cultural Differences as Excuses? Human Rights and Cultural Values in Global Ethics and Governance of AI. Philosophy & Technology. §16.7 §66.1 §F.20
- (2014). Sketching as a Tool for Numerical Linear Algebra. Foundations and Trends® in Theoretical Computer Science. doi:10.1561/0400000060. §F.11
- (1964). WMA Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Participants. World Medical Association. non-peer-reviewed §21.7 §64.5 §F.36
- (2025). Estimating the Probabilities of Rare Outputs in Language Models. International Conference on Learning Representations. §6.6 §47.5 §47.8 §F.2
- (2025). Provable Weak-to-Strong Generalization via Benign Overfitting. International Conference on Learning Representations. §9.2 §42.2 §42.6 §42.7 §42.8 §F.2 §H.1
- (2021a). How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals. Nature Medicine. §F.36
- (2021b). Recursively Summarizing Books with Human Feedback. arXiv. preprint §41.2 §F.6
- (2024a). Do language models plan ahead for future tokens? arXiv. preprint §F.2
- (2024b). Retrieval Head Mechanistically Explains Long-Context Factuality. International Conference on Learning Representations. §F.7
- (2024c). The Semantic Hub Hypothesis: Language Models Share Semantic Representations Across Languages and Modalities. International Conference on Learning Representations. §F.7
- (2025a). AI shares emotion with humans across languages and cultures. arXiv. preprint §F.11
- (2025b). AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders. International Conference on Machine Learning. §44.7 §44.8 §46.1 §46.2 §46.9 §F.7
- (2025c). Dissecting Adversarial Robustness of Multimodal LM Agents. International Conference on Learning Representations. §49.2 §F.8
- (2025d). Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy. International Conference on Learning Representations. §19.3 §19.9 §49.4 §F.8
- (2025e). IsolateGPT: An Execution Isolation Architecture for LLM-Based Systems. Proceedings 2025 Network and Distributed System Security Symposium. §49.2 §49.6 §F.8
- (2025f). When More is Less: Understanding Chain-of-Thought Length in LLMs. arXiv. preprint §F.6
X
- (2025a). Grok prompts. GitHub (xai-org). non-peer-reviewed §4.1 §38.5 §51.1 §53.5 §54.5 §68.1 §C.7 §F.45
- (2025b). We want to update you on an incident that happened with our Grok response bot on X yesterday. non-peer-reviewed §38.5 §53.5 §68.1 §C.7 §F.13
- (2025c). xAI Risk Management Framework. xAI. non-peer-reviewed §62.5 §F.13 §I.2
- (2021). An Explanation of In-context Learning as Implicit Bayesian Inference. International Conference on Learning Representations. §6.1 §11.3 §11.6 §F.2
- (2024a). GradSafe: Detecting Jailbreak Prompts for LLMs via Safety-Critical Gradient Analysis. Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/2024.acl-long.30. §F.8
- (2024b). SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal. International Conference on Learning Representations. §20.3 §F.3
- (2023). Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs. International Conference on Learning Representations. §6.4 §F.2
- (2020). Recipes for Safety in Open-domain Chatbots. arXiv. preprint §F.11
- (2021). Detoxifying Language Models Risks Marginalizing Minority Voices. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. §20.3 §27.3 §27.9 §F.12
- (2025). TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks. Advances in Neural Information Processing Systems 38. §68.5 §F.10
- (2026). Studying metagaming latents in language models. OpenAI Alignment Research Blog. non-peer-reviewed §33.1 §33.4 §37.4 §37.10 §E.5 §F.5
- (2014). Xunzi. Princeton University Press. §20.5 §F.20
Y
- (2025). Addition in Four Movements: Mapping Layer-wise Information Trajectories in LLMs. Conference on Empirical Methods in Natural Language Processing. §F.11
- (2024a). Asymptotics of Language Model Alignment. 2024 IEEE International Symposium on Information Theory (ISIT). doi:10.1109/isit57864.2024.10619456. §F.2
- (2024b). Do Large Language Models Latently Perform Multi-Hop Reasoning? Annual Meeting of the Association for Computational Linguistics. §F.2
- (2024c). Super(ficial)-alignment: Strong Models May Deceive Weak Models in Weak-to-Strong Generalization. arXiv. preprint §42.6 §42.7 §42.8 §F.6 §H.2
- (2024d). Weak-to-Strong Reasoning. Conference on Empirical Methods in Natural Language Processing. §42.3 §42.6 §42.8 §F.6
- (2025a). Qwen3 Technical Report. arXiv. preprint §F.11
- (2025b). Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning. Neural Information Processing Systems. §F.11
- (2026). Zombie Agents: Persistent Control of Self-Evolving LLM Agents via Self-Reinforcing Injections. arXiv. preprint §49.7 §49.10 §F.8
- (2022). ReAct: Synergizing Reasoning and Acting in Language Models. International Conference on Learning Representations. §11.5 §F.2
- (2023a). Large Language Model Unlearning. Advances in Neural Information Processing Systems. §27.7 §F.4
- (2023b). Tree of Thoughts: Deliberate Problem Solving with Large Language Models. Advances in Neural Information Processing Systems. §F.2
- (2026). Prompt Injection as Role Confusion. arXiv. preprint §49.1 §49.4 §49.10 §F.8
- (2023). AttentionViz: A Global View of Transformer Attention. IEEE Transactions on Visualization and Computer Graphics. doi:10.1109/TVCG.2023.3327163. §F.2
- (2019). Average firing rate rather than temporal pattern determines metabolic cost of activity in thalamocortical relay neurons. Scientific Reports. §F.7
- (2025). Benchmarking and Defending against Indirect Prompt Injection Attacks on Large Language Models. Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1. §49.1 §49.5 §49.10 §F.8 §H.2
- (2024). Transmission Versus Truth, Imitation Versus Innovation: What Children Can Do That Large Language and Language-and-Vision Models Cannot (Yet). Perspectives on Psychological Science. §1.6 §11.7 §57.6 §F.43
- (2023). Low-Resource Languages Jailbreak GPT-4. arXiv. preprint §26.6 §26.7 §26.9 Ch. 26 §31.5 §31.9 §36.4 §48.2 §48.9 §F.8 §H.2
- (2015). Understanding Neural Networks Through Deep Visualization. arXiv. preprint §F.2
- (2022). Confronting Power and Corporate Capture at the FAccT Conference. 2022 ACM Conference on Fairness Accountability and Transparency. §5.6 §61.6 §F.12
- (2025). Towards Safeguarding LLM Fine-tuning APIs against Cipher Attacks. arXiv. preprint §F.8
- (2023). GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts. arXiv. preprint §F.8
- (2024a). Arctic-Embed 2.0: Multilingual Retrieval Without Compromise. arXiv. preprint §F.11
- (2024b). MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models. Advances in Neural Information Processing Systems. §F.2
- (2025). Back Attention: Understanding and Enhancing Multi-Hop Reasoning in Large Language Models. Conference on Empirical Methods in Natural Language Processing. §F.2
- (2025). From Hard Refusals to Safe-Completions: Toward Output-Centric Safety Training. arXiv. preprint §20.1 §20.8 §23.3 §F.4
- (2004). Coherent Extrapolated Volition. The Singularity Institute, San Francisco, CA. non-peer-reviewed §2.3 §2.8 §2.9 §3.2 §16.2 §16.11 §70.3 §C.3 §F.42
- (2008). Artificial Intelligence as a positive and negative factor in global risk. Global Catastrophic Risks. §2.2 §2.3 §2.8 §3.2 §C.3 §F.42
- (2013). Intelligence Explosion Microeconomics. Machine Intelligence Research Institute (technical report). non-peer-reviewed §2.3 §C.3 §F.1
- (2022). AGI Ruin: A List of Lethalities. AI Alignment Forum. non-peer-reviewed §2.6 §3.1 §3.2 §3.8 §3.9 Ch. 3 §4.3 Ch. 4 §5.8 §31.7 §50.4 §50.6 §51.4 §51.6 Ch. 51 §70.3 §70.7 Ch. 70 §C.5 §F.14
- (2023). GPTs are Predictors, not Imitators. AI Alignment Forum. non-peer-reviewed §11.7 §F.14
- (2013). Tiling Agents for Self-Modifying AI, and the Löbian Obstacle. Machine Intelligence Research Institute (early draft). working paper §7.6 §55.1 §F.24
- (2017). Functional Decision Theory: A New Theory of Instrumental Rationality. arXiv. preprint §3.2 §7.2 §7.6 Ch. 7 §F.24
- (2025). If Anyone Builds It, Everyone Dies. Little, Brown and Company. §3.2 §3.8 §4.3 §5.8 §64.8 §65.5 §70.7 §C.7 §F.43
- (2023). Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning. arXiv. preprint §F.7
- (2025). Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model? arXiv. preprint §12.7 Ch. 12 §24.4 §24.9 Ch. 24 §F.2
- (2026). Reasoning Models Struggle to Control their Chains of Thought. arXiv. preprint §40.4 §40.8 §E.5 §F.6
- (2021). Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors. Workshop on Knowledge Extraction and Integration for Deep Learning Architectures; Deep Learning Inside Out. doi:10.18653/V1/2021.DEELIO-1.1. §44.1 §44.5 §F.7
Z
- (2021). International Control of Powerful Technology: Lessons from the Baruch Plan for Nuclear Weapons. Centre for the Governance of AI. working paper §64.1 §64.3 §64.10 Ch. 64 §F.30
- (1981). Feedback and optimal sensitivity: Model reference transformations, multiplicative seminorms, and approximate inverses. IEEE Transactions on Automatic Control. §F.21
- (2025). Trading Inference-Time Compute for Adversarial Robustness. arXiv. preprint §F.8
- (1997). Four dark corners of requirements engineering. ACM Transactions on Software Engineering and Methodology. §19.1 §19.9 Ch. 19 §24.2 §24.10 Ch. 24 §D.10 §F.50
- (2000). A reference model for requirements and specifications. IEEE Software. §F.50
- (2013). Visualizing and Understanding Convolutional Networks. European Conference on Computer Vision. doi:10.1007/978-3-319-10590-1_53. §F.11
- (2019). HellaSwag: Can a Machine Really Finish Your Sentence? Annual Meeting of the Association for Computational Linguistics. doi:10.18653/v1/P19-1472. §F.11
- (2024). InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents. Findings of the Association for Computational Linguistics ACL 2024. doi:10.18653/v1/2024.findings-acl.624. §49.3 §49.5 §F.8
- (2025). Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents. Findings of the Association for Computational Linguistics: NAACL 2025. §48.1 §49.5 §49.10 §70.3 §F.8 §H.2
- (2023). Towards Best Practices of Activation Patching in Language Models: Metrics and Methods. International Conference on Learning Representations. §43.4 §43.8 §45.8 §F.7 §H.2
- (2019). Root Mean Square Layer Normalization. Advances in Neural Information Processing Systems. doi:10.5167/UZH-177483. §8.2 §F.2
- (2025). Decoding Emotion in the Deep: A Systematic Study of How LLMs Represent, Retain, and Express Emotion. arXiv. preprint §F.11
- (2016). Understanding deep learning requires rethinking generalization. arXiv. preprint §8.4 Ch. 8 §9.1 §9.2 Ch. 9 §F.2
- (2019). Word Embedding Visualization Via Dictionary Learning. arXiv. preprint §F.7
- (2022). Forecasting AI Progress: Evidence from a Survey of Machine Learning Researchers. arXiv. preprint §F.28
- (2023). Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding. arXiv. preprint §F.2
- (2024a). A Careful Examination of Large Language Model Performance on Grade School Arithmetic. Advances in Neural Information Processing Systems. §15.7 §36.5 §F.48
- (2024b). Agent-SafetyBench: Evaluating the Safety of LLM Agents. arXiv. preprint §49.3 §F.8
- (2024c). Harnessing Diversity for Important Data Selection in Pretraining Large Language Models. International Conference on Learning Representations. §F.2
- (2024d). Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models. arXiv. preprint §F.2
- (2024e). Persistent Pre-Training Poisoning of LLMs. International Conference on Learning Representations. §27.6 §48.6 §F.8
- (2024f). SafetyBench: Evaluating the Safety of Large Language Models. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). §F.6
- (2024g). The Same But Different: Structural Similarities and Differences in Multilingual Language Modeling. International Conference on Learning Representations. §F.2
- (2025a). Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models. International Conference on Learning Representations. §58.3 §58.10 §F.9
- (2025b). EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification. Neural Information Processing Systems. §F.7
- (2025c). Stress-Testing Model Specs Reveals Character Differences among Language Models. arXiv. preprint §19.2 §19.4 §19.8 §19.9 §20.6 §23.6 §26.5 §E.3 §F.4
- (2026a). A3: An Automated Alignment Agent for Safety Finetuning. Anthropic Alignment Science Blog. non-peer-reviewed §E.3 §F.58 §I.5
- (2026b). AgentWorm: Self-Propagating Attacks Across LLM Agent Ecosystems. arXiv. preprint §49.7 §57.6 §57.7 §57.9 §F.8 §H.2
- (2021a). Calibrate Before Use: Improving Few-Shot Performance of Language Models. International Conference on Machine Learning. §F.6
- (2021b). Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions? Findings. doi:10.18653/v1/2021.findings-acl.364. §F.2
- (2024). WildChat: 1M ChatGPT Interaction Logs in the Wild. International Conference on Learning Representations. §60.1 §F.9
- (2025). Learning to Reason without External Rewards. arXiv. preprint §24.4 §24.9 §F.4
- (2023a). Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. Advances in Neural Information Processing Systems. doi:10.52202/075280-2020. §36.6 §36.10 §F.6
- (2023b). LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. International Conference on Learning Representations. §60.1 §F.9
- (2024). Attention Heads of Large Language Models: A Survey. Patterns. doi:10.1016/j.patter.2025.101176. §F.2
- (2025). Beyond Preferences in AI Alignment. Philosophical Studies. §1.1 §13.6 Ch. 13 §16.8 Ch. 16 §22.8 §F.42
- (2025). Watch the Weights: Unsupervised monitoring and control of fine-tuned LLMs. arXiv. preprint §F.6
- (2023). The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks. Advances in Neural Information Processing Systems. §45.2 §45.7 §45.8 §F.7 §H.2
- (2024a). Beyond English-Centric LLMs: What Language Do Multilingual Language Models Think in? arXiv. preprint §F.2
- (2024b). Evaluation of OpenAI o1: Opportunities and Challenges of AGI. arXiv. preprint §F.6
- (2025). ImpossibleBench: Measuring LLMs' Propensity of Exploiting Test Cases. arXiv. preprint §24.2 §24.9 §36.1 §36.5 §F.4
- (2014). Object Detectors Emerge in Deep Scene CNNs. International Conference on Learning Representations. §F.11
- (2019). Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask. Advances in Neural Information Processing Systems. §F.11
- (2022). Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. International Conference on Learning Representations. §F.2
- (2023a). Instruction-Following Evaluation for Large Language Models. arXiv. preprint §F.6
- (2023b). LIMA: Less Is More for Alignment. Advances in Neural Information Processing Systems. §11.4 §F.2
- (2023c). What Algorithms can Transformers Learn? A Study in Length Generalization. International Conference on Learning Representations. §F.2
- (2024a). How Alignment and Jailbreak Work: Explain LLM Safety through Intermediate Hidden States. Conference on Empirical Methods in Natural Language Processing. §F.8
- (2024b). Larger and more instructable language models become less reliable. Nature. §4.1 §4.8 §5.8 §60.4 §F.9
- (2024c). Pre-trained Large Language Models Use Fourier Features to Compute Addition. Advances in Neural Information Processing Systems. §F.7
- (2020a). Blame-Laden Moral Rebukes and the Morally Competent Robot: A Confucian Ethical Perspective. Science and Engineering Ethics. §F.20
- (2020b). Modifying Memories in Transformer Models. arXiv. preprint §F.2
- (2023). Principled Reinforcement Learning with Human Feedback from Pairwise or -wise Comparisons. International Conference on Machine Learning. §12.8 §13.2 §13.3 §22.5 §F.2
- (2024). Language Models Represent Beliefs of Self and Others. International Conference on Machine Learning. §F.2
- (2025). MELON: Provable Defense Against Indirect Prompt Injection Attacks in AI Agents. International Conference on Machine Learning. §49.5 §F.8
- (2020). Consequences of Misaligned AI. Advances in Neural Information Processing Systems. §14.3 §15.4 §30.2 §F.25
- (2024). Vector-ICL: In-context Learning with Continuous Vector Representations. International Conference on Learning Representations. §F.7
- (2008). Maximum Entropy Inverse Reinforcement Learning. Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence. §13.2 §13.3 §22.1 §F.2
- (2019). Fine-Tuning Language Models from Human Preferences. arXiv. preprint §12.2 §12.3 §22.3 §F.2
- (2022). Adversarial Training for High-Stakes Reliability. Advances in Neural Information Processing Systems. §48.5 §F.8
- (2025a). Can Reasoning Models Obfuscate Reasoning? Stress-Testing Chain-of-Thought Monitorability. arXiv. preprint §40.4 §F.6
- (2025b). Early Signs of Steganographic Capabilities in Frontier LLMs. arXiv. preprint §40.5 §F.6
- (2023a). Representation Engineering: A Top-Down Approach to AI Transparency. arXiv. preprint §3.6 §39.5 §43.7 §46.2 §46.9 §F.7 §H.2
- (2023b). Universal and Transferable Adversarial Attacks on Aligned Language Models. arXiv. preprint §48.2 Ch. 48 §C.6 §F.8
- (2024). Improving Alignment and Robustness with Circuit Breakers. Advances in Neural Information Processing Systems. §48.5 §F.8
- (2025). Security Challenges in AI Agent Deployment: Insights from a Large Scale Public Competition. Advances in Neural Information Processing Systems 38. §49.3 §49.10 §56.5 §F.8 §H.2
- (2025). Can LLMs Separate Instructions From Data? And What Do We Even Mean By That? International Conference on Learning Representations. §19.3 §19.9 §49.1 §49.10 Ch. 49 §F.8
- (2019). Thinking About Risks From AI: Accidents, Misuse and Structure. Lawfare. non-peer-reviewed §4.1 §65.1 §68.1 §F.45