{"url":"/dataset/agenteval","name":"AgentEval","full_name":null,"description_markdown":"AgentEval is part of the AgentGym framework, which is designed to evaluate and develop generally-capable Large Language Model-based (LLM-based) agents. AgentEval serves as a benchmark suite within AgentGym, providing a set of tasks and environments to assess the performance of these agents¹².\r\n\r\nThe AgentGym framework includes diverse interactive environments and tasks with a unified format, supporting real-time feedback and concurrency, which is essential for the development and scaling of LLM-based agents. The benchmark suite, AgentEval, along with the trajectory sets AgentTraj and AgentTraj-L, enables researchers and developers to measure the capabilities of agents across a broad spectrum of tasks and environments².\r\n\r\n(1) AgentGym: Evolving Large Language Model-based Agents across Diverse .... https://arxiv.org/html/2406.04151v1.\r\n(2) GitHub - WooooDyy/AgentGym: Code and implementations for the paper .... https://github.com/WooooDyy/AgentGym.\r\n(3) AgentGym: Evolving Large Language Model-based Agents across Diverse .... https://agentgym.github.io/.\r\n(4) undefined. https://agentgym.github.io.","description_withheld":null,"homepage":"https://github.com/WooooDyy/AgentGym","introduced_date":"2024-06-06","introduced_date_note":null,"introduced_by":{"paper":"/paper/agentgym-evolving-large-language-model-based","title":"AgentGym: Evolving Large Language Model-based Agents across Diverse Environments","first_author":"Zhiheng Xi","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["AgentEval"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}