---
id: 20260808-T0-08
title: "Woodpecker蒸馏：用弱模型定位强模型推理中的局部错误"
title_en: "Woodpecker Distillation: Weak Models Diagnose Reasoning Bugs in Strong Models"
url: https://ai.daily.yangsir.net/daily/20260808-T0-08
issue_date: 2026-08-08
publish_date: 2026-08-07T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2608.05168
---

# Woodpecker蒸馏：用弱模型定位强模型推理中的局部错误

arXiv新论文提出Woodpecker蒸馏方法，核心发现是大模型在推理任务中的失败往往源于中间步骤的局部错误，而非整体能力不足。该方法利用弱模型来诊断强模型推理过程中的具体错误位置，为改进大模型推理能力提供了新思路。

## English Version

**Woodpecker Distillation: Weak Models Diagnose Reasoning Bugs in Strong Models**

New arXiv paper introduces Woodpecker Distillation, showing that LLM reasoning failures often stem from localized bugs in intermediate steps rather than global incompetence. The method uses weak models to diagnose specific error locations in stronger models, offering a new approach to improving LLM reasoning.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2608.05168)

**详情页**：https://ai.daily.yangsir.net/daily/20260808-T0-08

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