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ReplicHAI › Agent Evals › 11 Continual learning, memory & multi-agent

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Year ↓ Title added Authors Venue
Webpage 2026 Continual Learning Bench (site and leaderboard) Berkeley
Preprint 2026 Continual Learning Bench: Evaluating Frontier AI Systems in Real-World Stateful Environments Asawa et al. arXiv
Preprint 2026 EmbodiedCLBench: Evaluating Continual Learning for Self-Evolving Embodied Agents Huang et al. arXiv
Preprint 2026 Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions Hu et al. arXiv
Preprint 2026 Mem2ActBench: A Benchmark for Evaluating Long-Term Memory Utilization in Task-Oriented Autonomous Agents Shen et al. arXiv
Preprint 2026 SkillLearnBench: Benchmarking Continual Learning Methods for Agent Skill Generation on Real-World Tasks Zhong et al. arXiv
Preprint 2026 When Does Memory Help? A Cost-Aware Evaluation of Long-Term Memory in Tool-Using LLM Agents Mishra, Mishra arXiv
Preprint 2025 LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory Wu et al. arXiv
Preprint 2025 MemBench: Towards More Comprehensive Evaluation on the Memory of LLM-based Agents Tan et al. arXiv
Preprint 2025 MultiAgentBench: Evaluating the Collaboration and Competition of LLM agents Zhu et al. arXiv
Preprint 2025 Why Do Multi-Agent LLM Systems Fail? Cemri et al. arXiv
Preprint 2024 Evaluating Very Long-Term Conversational Memory of LLM Agents Maharana et al. arXiv
Preprint 2024 StreamBench: Towards Benchmarking Continuous Improvement of Language Agents Wu et al. arXiv

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