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arXiv AI By Chengyu Yang, Yunxiang Zheng, Zongzheng Li, Jiamei Li, Boxun Lan, Xiaoyu Liu, Xiaoyu Zhang, Xiaohong Chen, Ming Hu

Compile Away Uncertainty: Self-Evolving Agent Skills via Programmatic Compilation

Read the original on arXiv AI →

The paper introduces SkillCompiler, a framework that compiles self‑evolving agent skills into deterministic programs to reduce uncertainty from LLM reasoning. It decomposes skills into fine‑grained operations, selectively compiles well‑specified parts into validated programs, and reuses these programs across evolving skills. Experiments on five benchmarks and six model families show SkillCompiler outperforms state‑of‑the‑art methods, achieving up to a 32.33% improvement in task performance.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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