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Oct 12 · Monday
Another 255 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.
揭示推理加深引发的对齐坍塌,用 Reasoning Trap 放大越狱
Published Sep 8
Evaluated models Qwen3-8B , Qwen3-14B , Llama2-7B and others8 Abstract 更深推理提升题目准确率,同时提高扰动下的相对损失。作者研究扩展推理是否以对齐稳健性为代价,提出 ALR、RT 与 RRA。 。
分析续写触发越狱的注意力头机制并提出 HCS
Published Mar 9
Evaluated models LLaMA-2-7B-Chat , Qwen2.5-7B-Instruct Abstract 作者称越狱来自两类头竞争,HCS 加蒸馏可把该竞争用于推理时干预。作者用注意力头机制分析 continuation-triggered jailbreak:同一有害指令下,把 continuation 后缀从指令后面挪到提示词边界外,模型更容易顺着后缀继续生成。
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