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Author

Chao-Ran Chen

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Preprint Aug 2026

Retry, Switch, or Abstain? Learning Strategy-Aware Tool-Use Policies via Controlled Error Injection

Tool-using LLM agents are commonly trained and evaluated in environments where tool calls succeed reliably, yet deployed tools can fail transiently, persistently, or silently. Robust recovery therefore requires more than repeated retries: an agent may need to retry the same path, switch to an alternative, or recognize...

Chao-Ran Chen, Vylinh J. Nguyen, Zi-Ji Zhang et al. · 2 citations

How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions

An observational study of 20,574 coding-agent sessions from 1,639 repositories across IDE and CLI workflows operationalizes misalignment as a breakdown made visible through developer pushback, and annotates each episode along four axes: form, cause, cost, and resolution.

Ningzhi Tang, Chaoran Chen, Gelei Xu et al. · 10 citations · ⚡1

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