agent-eto/eto-sft-trajectory
Expert Trajectories for ETO π Homepage | π GitHub | π arXiv Expert trajectories for Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents Authors: Yifan Song, Da Yin, Xiang Yue, Jie Huang, Sujian Li, Bill Yuchen Lin. We introduce ETO (Exploration-based Trajectory Optimization), an agent learning framework inspired by "trial and error" process of human learning. ETO allows an LLM agent to iteratively collect failure trajectories and updates its policyβ¦ See the full description on the dataset page: https://huggingface.co/datasets/agent-eto/eto-sft-trajectory.
| Author / organization | agent-eto |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 426 (as reported by Hugging Face) |
| Likes | 19 |
| Created | 9 April 2024 |
| Last updated at source | 9 April 2024 |
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- 16 Oct 2026 Description: Expert Trajectories for ETO π Homepage | π GitHub | π arXiv Expert trajectories for Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents Authors: Yifan Song, Da Yin, Xiang Yue, Jie Huang, Sujian Li, Bill Yuchen Lin. β Expert Trajectories for ETO π Homepage | π GitHub | π arXiv Expert trajectories for Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents Authors: Yifan Song, Da Yin, Xiang Yue, Jie Huang, Sujian Li, Bill Yuchen Lin.
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