---
id: 20260507-T0-06
title: "研究发现AI安全模型在微调中会失去保护能力"
title_en: "Study: AI Safety Models Lose Protection After Fine-Tuning"
url: https://ai.daily.yangsir.net/daily/20260507-T0-06
issue_date: 2026-05-07
publish_date: 2026-05-06T04:00:00.000Z
category: research
source_name: "arXiv cs.LG (ML)"
source_url: https://arxiv.org/abs/2605.02914
---

# 研究发现AI安全模型在微调中会失去保护能力

arXiv论文发现，使用完全良性数据微调的安全模型会失去所有安全对齐能力。这种现象不是通过对抗性攻击造成的，而是通过标准领域专业化导致的。研究在LlamaGuard、SafetyRL和Honesty三个安全分类器中验证了这一失败模式，对AI安全部署提出了重要警示。

## English Version

**Study: AI Safety Models Lose Protection After Fine-Tuning**

An arXiv paper reveals that safety models fine-tuned on entirely benign data can lose all safety alignment—not through adversarial attacks, but through standard domain specialization. The study validates this failure pattern across three safety classifiers (LlamaGuard, SafetyRL, and Honesty), raising important warnings for AI safety deployment.

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**来源**：[arXiv cs.LG (ML)](https://arxiv.org/abs/2605.02914)

**详情页**：https://ai.daily.yangsir.net/daily/20260507-T0-06

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