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When History Fails to Become Experience: Action Calibration in Language Agents

Language agents should draw on prior attempts and environmental feedback to improve subsequent decisions within the same task. However, providing additional interaction history can sometimes reduce task success, suggesting that agents do not consistently use this information effectively.

By Jingyu Liu, Zhiwen Wang, Yuxin Jing, Huanyu Zhou, Yong LiuarXiv - cs.CL (NLP)

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Originally published by arXiv - cs.CL (NLP) on Oct 5, 2026.

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