---
id: 20260819-T0-05
title: "SKILL框架：让LLM代理以自我纠正方式优化逻辑电路"
title_en: "SKILL: Self-Correcting LLM Agent for Logic Optimization"
url: https://ai.daily.yangsir.net/daily/20260819-T0-05
issue_date: 2026-08-19
publish_date: 2026-08-18T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2608.14579
---

# SKILL框架：让LLM代理以自我纠正方式优化逻辑电路

arXiv新论文提出SKILL框架，让大语言模型代理在逻辑综合优化中通过知识引导和自我纠正进行迭代。传统专家设计流程缺乏适应性，强化学习方法面临探索空间大、奖励信号稀疏等问题。SKILL利用LLM的通用推理能力解决这些挑战，为芯片设计自动化中的逻辑优化提供了新思路。

## English Version

**SKILL: Self-Correcting LLM Agent for Logic Optimization**

A new arXiv paper introduces SKILL, a framework enabling LLM agents to perform iterative logic optimization through knowledge-guided self-correction. Traditional expert-designed flows lack adaptability, while RL methods struggle with large search spaces and sparse rewards. SKILL leverages LLM reasoning to address these challenges, offering a fresh approach to logic synthesis in chip design automation.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2608.14579)

**详情页**：https://ai.daily.yangsir.net/daily/20260819-T0-05

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