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Oct 12 · Monday
Another 261 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.
提出主题锚点投毒,放大众包微调后的专有指令提取
Published Sep 28
Evaluated models Qwen2.5-7B-Instruct , Qwen2.5-14B-Instruct , Llama-3.1-8B-Instruct and others4 Abstract 论文提出基于主题锚点的数据中毒攻击,证明低比例的中毒样本可在黑盒条件下隐蔽放大微调指令泄漏。
用编码与结构化请求抽取系统指令,并用 CoT 改写加固
Published Apr 1
Evaluated models GPT-4.1-mini , GPT-3.5-turbo , Gemini-2.5-flash and others7 Abstract 编码式请求可在直接拒答后引出系统指令。这项工作评测并加固 LLM 系统指令在编码式抽取下的保密性。作者关心的是:直接抽取已被拒绝时,把同一请求改写成格式化或编码任务,模型是否仍交出受保护内容。
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