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Oct 12 · Monday
Another 265 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.
分析文本水印在 RAG 中诱发事实幻觉的机制并提出干预
Published Oct 4
Evaluated models LLaMA 3.1 8B Instruct , Mistral-7B-Instruct-v0.3 , Qwen2.5-14B-Instruct Abstract 论文揭示了生产环境文本水印导致模型事实退化的失效模式，分析了解码机制并提出针对性干预。论文研究生产级文本水印对大语言模型事实准确性的影响，分析了水印诱发幻觉的失效模式并评估了针对性缓解方案。
提出 KPI，用入度定位跨层关键路径并做 SAE 转向以解决知识冲突
Published Sep 8
Evaluated models Llama-3-8B , Llama-3.1-8B , Gemma-2-9B Abstract KPI 以入度关键路径替代大批 SAE 特征转向，在冲突 RAG 上提高忠实并减轻副作用。KPI 针对知识冲突 RAG 中的 SAE 转向：相关性批量改特征会带入冗余，少量因果上关键的特征即可完成转向。
提出软提示防御 AREA，重锚定注意力以缓解系统提示泄露
Published Jun 17
Evaluated models Llama-2-7B-chat-hf , Llama-3.1-8B-Instruct , Mistral-7B-Instruct-v0.3 and others8 Abstract 作者测量商用提示词泄漏，提出 attention drift，并用 AREA 在可用性与抗泄漏间取折中。作者研究真实 LLM 应用中的 system prompt 泄漏 ，并给出不改权重的缓解方法 AREA。
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