Datasets › AgentEval
AgentEval
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.
The 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.
(1) AgentGym: Evolving Large Language Model-based Agents across Diverse .... https://arxiv.org/html/2406.04151v1. (2) GitHub - WooooDyy/AgentGym: Code and implementations for the paper .... https://github.com/WooooDyy/AgentGym. (3) AgentGym: Evolving Large Language Model-based Agents across Diverse .... https://agentgym.github.io/. (4) undefined. https://agentgym.github.io.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
No task tagged in the archive.
License archive 2025-07-28
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Modalities archive 2025-07-28
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Languages archive 2025-07-28
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Variants archive 2025-07-28
- AgentEval
1 variant name, as the archive lists them.
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