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Oct 13 · Tuesday
Another 227 papers do not have category tags yet and are not included in filtered results.
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About this collection Collection in progress We are building a large AI safety paper collection to help researchers find work related to their interests. Papers are collected automatically andfiltered only for relevance to AI safety , without judging quality, novelty or reading value. The default “Annotated first” shows papers with tags or published paper analyses first. Each group is ordered by original publication date, newest first, with undated papers last. “Newest first” uses publication dates only. This order is not a quality ranking.
One-line summaries, tags and paper analyses are prepared by AI from the papers. Language models may have systematic biases and produce hallucinations.We plan to carry out human annotation and review to reduce errors in this content.
提出 ReSA，从对齐模型行为恢复安全奖励并在解码时反转
Published Oct 6
Evaluated models Llama3.1-8B-Instruct , Gemma-7B-Instruct , Qwen2.5-7B-Instruct and others9 Abstract ReSA 用最大熵 IRL 从对齐模型行为恢复代理安全奖励，并在解码时反转以诱导有害输出。ReSA 是一种对抗攻击：从对齐模型的可观察行为恢复代理安全奖励，再在解码时把该奖励反过来用。 。
提出 INFER+ 信息过载方法，越狱大型视觉语言模型
Published Jul 3
Evaluated models Qwen3-VL-8B , Qwen2-VL-7B , InternVL3.5-8B and others8 Abstract 用图文过载越狱 LVLM。这篇工作用信息过载 越狱 LVLM，而不是靠 OOD 变换隐藏意图。
提出 ASO，用 GRPO 优化视觉风格以放大越狱攻击
Published Jun 1
Evaluated models GPT-4.1-mini , Gemini-2.5-Flash , Qwen3-VL and others6 Abstract 论文揭示了 MLLM 的风格敏感性脆弱面，提出 ASO 框架利用强化学习优化风格触发器，有效放大了现有视觉越狱效果。
Attacks arXiv 2503.02174 · Mar 4, 2025 提出 AdvTok 对抗分词攻击，不改文本只改分词来越狱并规避安全分类器
Published Mar 4, 2025
Evaluated models Llama3.2-1B , Llama3.2-3B , Llama3.1-8B and others7 Abstract 作者称非规范分词能躲开对齐并仍得到针对原请求的回复。作者用非规范分词攻击已对齐的子词 LLM：恶意字符串的字符不变，只改 token 边界。
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