|
2024 |
LMArena |
LMArena |
|
|
2024 |
Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks |
Fourney et al. |
arXiv |
|
2024 |
METR Task Standard |
METR |
|
|
2024 |
ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code |
Tang et al. |
arXiv |
|
2024 |
MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation |
Huang et al. |
arXiv |
|
2024 |
OfficeBench: Benchmarking Language Agents across Multiple Applications for Office Automation |
Wang et al. |
arXiv |
|
2024 |
OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web |
Kapoor et al. |
arXiv |
|
2024 |
OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments |
Xie et al. |
arXiv |
|
2024 |
Prompting Large Language Models to Tackle the Full Software Development Lifecycle: A Case Study |
Li et al. |
arXiv |
|
2024 |
Raising the bar on SWE-bench Verified with Claude 3.5 Sonnet |
Anthropic |
|
|
2024 |
RedCode: Risky Code Execution and Generation Benchmark for Code Agents |
Guo et al. |
arXiv |
|
2024 |
SciCode: A Research Coding Benchmark Curated by Scientists |
Tian et al. |
arXiv |
|
2024 |
SEAL Leaderboards |
AI |
|
|
2024 |
SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents |
Cheng et al. |
arXiv |
|
2024 |
Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows? |
Cao et al. |
arXiv |
|
2024 |
SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation |
Ma et al. |
arXiv |
|
2024 |
StreamBench: Towards Benchmarking Continuous Improvement of Language Agents |
Wu et al. |
arXiv |
|
2024 |
SUPER: Evaluating Agents on Setting Up and Executing Tasks from Research Repositories |
Bogin et al. |
arXiv |
|
2024 |
SWE-bench Multimodal: Do AI Systems Generalize to Visual Software Domains? |
Yang et al. |
arXiv |
|
2024 |
SWE-Bench+: Enhanced Coding Benchmark for LLMs |
Aleithan et al. |
arXiv |
|
2024 |
SWE-bench: Can Language Models Resolve Real-World GitHub Issues? |
Jimenez et al. |
arXiv |
|
2024 |
TravelPlanner: A Benchmark for Real-World Planning with Language Agents |
Xie et al. |
arXiv |
|
2024 |
VisualAgentBench: Towards Large Multimodal Models as Visual Foundation Agents |
Liu et al. |
arXiv |
|
2024 |
VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks |
Koh et al. |
arXiv |
|
2024 |
WebArena: A Realistic Web Environment for Building Autonomous Agents |
Zhou et al. |
arXiv |
|
2024 |
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue |
Lù et al. |
arXiv |
|
2024 |
WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models |
He et al. |
arXiv |
|
2024 |
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale |
Bonatti et al. |
arXiv |
|
2024 |
WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks? |
Drouin et al. |
arXiv |
|
2023 |
API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs |
Li et al. |
arXiv |
|
2023 |
CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion |
Ding et al. |
arXiv |
|
2023 |
GAIA: a benchmark for General AI Assistants |
Mialon et al. |
arXiv |
|
2023 |
Gorilla: Large Language Model Connected with Massive APIs |
Patil et al. |
arXiv |
|
2023 |
Holistic Evaluation of Language Models |
Liang et al. |
arXiv |
|
2023 |
InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback |
Yang et al. |
arXiv |
|
2023 |
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning |
Liu et al. |
arXiv |
|
2023 |
Mind2Web: Towards a Generalist Agent for the Web |
Deng et al. |
arXiv |
|
2023 |
OpenAI Evals |
OpenAI |
|
|
2023 |
RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems |
Liu et al. |
arXiv |
|
2023 |
ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs |
Qin et al. |
arXiv |
|
2023 |
ToolQA: A Dataset for LLM Question Answering with External Tools |
Zhuang et al. |
arXiv |
|
2023 |
WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents |
Yao et al. |
arXiv |
|
2022 |
Benchmarking the Spectrum of Agent Capabilities |
Hafner |
arXiv |
|
2022 |
Competition-Level Code Generation with AlphaCode |
Li et al. |
Science |
|
2022 |
DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation |
Lai et al. |
arXiv |
|
2022 |
MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge |
Fan et al. |
arXiv |
|
2022 |
ScienceWorld: Is your Agent Smarter than a 5th Grader? |
Wang et al. |
arXiv |
|
2021 |
ALFWorld: Aligning Text and Embodied Environments for Interactive Learning |
Shridhar et al. |
arXiv |
|
2021 |
Evaluating Large Language Models Trained on Code |
Chen et al. |
arXiv |
|
2021 |
lm-evaluation-harness |
EleutherAI |
|
|
2021 |
Measuring Coding Challenge Competence With APPS |
Hendrycks et al. |
arXiv |
|
2021 |
Program Synthesis with Large Language Models |
Austin et al. |
arXiv |
|
2020 |
The NetHack Learning Environment |
Küttler et al. |
arXiv |
|
2019 |
TextWorld: A Learning Environment for Text-based Games |
Côté et al. |
arXiv |
|
2018 |
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration |
Liu et al. |
arXiv |
|
2016 |
OpenAI Gym |
Brockman et al. |
arXiv |