arxiv
PublishedApril 24, 2026 at 4:00 AM
—neutral
Survey on Evaluation of LLM-based Agents
Publisher summary· verbatim
arXiv:2503.16416v2 Announce Type: replace Abstract: LLM-based agents represent a paradigm shift in AI, enabling autonomous systems to plan, reason, and use tools while interacting with dynamic environments. This paper provides the first comprehensive survey of evaluation methods for these increasing
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivBringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning8harxivSubagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks8harxivDistribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts8harxivIn RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning8hThe Bubble Brief
WEEKLYRead evaluation insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗