Overview

AI agent evaluation studies how well systems use tools and interact with changing environments to complete tasks, from coding and web navigation to scientific and professional workflows. Researchers build interactive benchmarks and assess outcomes alongside execution traces, using deterministic state checks, expert rubrics, and language-model judges. Repeated trials and process-level measures help reveal failures in tool use, safety, consistency, and recovery that a final pass rate can hide. A central challenge is ensuring that benchmark scores reflect real capability rather than leakage, reward hacking, evaluator bias, or quirks of a particular model harness.

Latest papers

CardsList

525 papers77 papers in the last four weeks, up 4% on the four weeks before. 0.4% of all new papers.

  1. Video-Based Reward Modeling for Computer-Use Agents

    Mar 10, 2026Linxin Song, Jieyu Zhang, Huanxin Sheng +6Computer-Use Agent EvaluationReward Modeling

  2. Beyond Scaling: Assessing Strategic Reasoning and Rapid Decision-Making Capability of LLMs in Zero-sum Environments

    Mar 10, 2026Yang Li, Xing Chen, Yutao Liu +5AI Agent EvaluationAI Agent Benchmarks

  3. MASEval: Extending Multi-Agent Evaluation from Models to Systems

    Mar 9, 2026Cornelius Emde, Alexander Rubinstein, Anmol Goel +4AI Agent EvaluationAI Agent Benchmarks

  4. Evaluating Generalization Mechanisms in Autonomous Cyber Attack Agents

    Mar 6, 2026Ondřej Lukáš, Jihoon Shin, Emilia Rivas +6Generalization in RLAI Agent Evaluation

  5. Evaluating Multi-Agent LLM Architectures for Rare Disease Diagnosis

    Mar 6, 2026Ahmed AlmasoudMulti-Agent LLM SystemsAI Agent Evaluation

  6. AgentSCOPE: Evaluating Contextual Privacy Across Agentic Workflows

    Mar 5, 2026Ivoline C. Ngong, Keerthiram Murugesan, Swanand Kadhe +3AI Agent EvaluationAgentic Workflows

  7. A Multi-Agent Framework for Interpreting Multivariate Physiological Time Series

    Mar 4, 2026Davide Gabrielli, Paola Velardi, Stefano Faralli +1Explainable Artificial IntelligenceMulti-Agent LLMs

  8. A Rubric-Supervised Critic from Sparse Real-World Outcomes

    Mar 4, 2026Xingyao Wang, Valerie Chen, Heng Ji +1Reward ModelingAI Agent Evaluation

  9. Asymmetric Goal Drift in Coding Agents Under Value Conflict

    Mar 3, 2026Magnus Saebo, Spencer Gibson, Tyler Crosse +3AI Coding AgentsAI Agent Safety

  10. MOSAIC: A Universal Agent-Level Interface for Cross-Paradigm Agent Mixing and Human-AI Collaboration

    Mar 1, 2026Abdulhamid M. Mousa, Jinhui Pang, Rakhmonberdi Khajiev +5AI Agent EvaluationAgent Evaluation

  11. How Well Does Agent Development Reflect Real-World Work?

    Mar 1, 2026Zora Zhiruo Wang, Sanidhya Vijayvargiya, Aspen Chen +7AI Agent BenchmarksAI and Labor

  12. COMBAT: Conditional World Models for Behavioral Agent Training

    Feb 28, 2026Anmol Agarwal, Pranay Meshram, Sumer Singh +5Action-Conditioned World ModelsWorld Model Learning

  13. A Minimal Agent for Automated Theorem Proving

    Feb 27, 2026Borja Requena, Austin Letson, Krystian Nowakowski +2Large Language Model-Guided Theorem ProvingAutomated Theorem Proving

  14. Perfect score on IPhO 2025 theory by Gemini agent

    Feb 26, 2026Yichen HuangAI Agent EvaluationAI Agent Benchmarks

  15. Evaluating Stochasticity in Deep Research Agents

    Feb 26, 2026Haotian Zhai, Elias Stengel-Eskin, Pratik Patil +1Deep Research AgentsAI Agent Reliability

  16. AuditBench: Evaluating Alignment Auditing Techniques on Models with Hidden Behaviors

    Feb 26, 2026Abhay Sheshadri, Aidan Ewart, Elias Kempf +8Benchmark AuditingAI Agent Evaluation

  17. A Framework for Assessing AI Agent Decisions and Outcomes in AutoML Pipelines

    Feb 25, 2026Gaoyuan Du, Amit Ahlawat, Xiaoyang Liu +1AI Agent EvaluationAI Agent Auditing

  18. Aletheia tackles FirstProof autonomously

    Feb 24, 2026Tony Feng, Junehyuk Jung, Sang-hyun Kim +14LLM Mathematical ReasoningAutonomous Research Agents

  19. Implicit Intelligence -- Evaluating Agents on What Users Don't Say

    Feb 23, 2026Ved Sirdeshmukh, Marc WetterAI Agent EvaluationAI Agent Benchmarks

  20. Quantifying the Expectation-Realisation Gap for Agentic AI Systems

    Feb 23, 2026Sebastian LobentanzerAI Agent EvaluationHuman Oversight of AI

  21. MAS-FIRE: Fault Injection and Reliability Evaluation for LLM-Based Multi-Agent Systems

    Feb 23, 2026Jin Jia, Zhiling Deng, Zhuangbin Chen +2Multi-Agent LLM SystemsLLM Agent Reliability

  22. Anatomy of Agentic Memory: Taxonomy and Empirical Analysis of Evaluation and System Limitations

    Feb 22, 2026Dongming Jiang, Yi Li, Songtao Wei +8Agent MemoryAgent Memory Management