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Oct 13 · Tuesday
All papers Found 11 papers Another 215 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.
提出流匹配逆向框架，从多向量视觉文档索引重构页面
Published Oct 7
Evaluated models Tomoro-ColQwen3-8B , ColQwen3.5-4.5B , Tomoro-colqwen3-embed-4b and others13 评估应用决策层的输入注入与隐私推断风险
Published Oct 4
Evaluated models Jev , NanoJev Abstract Jev 的类型化决策可被输入与训练操纵，也会泄露信息，并同时支持检测与滥用。Jev 是 TypeSafe 的 System One 模型，把应用 state 和固定问题变成 Choice、Noul 或 Score 的类型化决策与概率。作者用官方 API 和可改训练的 NanoJev，考察它作为决策层时的操纵、泄露与双重用途。
提出 imMRAG 攻击，从多模态 RAG 私有图像库提取内容
Published Oct 1
Evaluated models Lumina-mGPT , Gemini 2.5 Flash Image Preview , CLIP ViT-B/16 and others5 提出 CIG-MIA，用上下文信息增益推断 RAG 知识库成员身份
Published Sep 14
Evaluated models Llama-3.1-8B-Instruct , Mistral-7B-Instruct-v0.3 , Llama-2-13b-chat-hf and others6 Abstract CIG-MIA 用注入前后的答案似然差推断 RAG 库成员，灰盒可分性高于所列基线。CIG-MIA 是针对 RAG 外部知识库的成员推断攻击，同时覆盖灰盒和纯文本黑盒。
Proposes SHAQ, which replaces document embeddings with shadow query embeddings to defend against embedding inversion.
Published Sep 4
Evaluated models GTR-T5 encoder , DPR Abstract SHAQ replaces document embeddings with shadow query embeddings.SHAQ is a defense against EIA for cloud vector databases: instead of directly modifying document embeddings, it replaces them with shadow query embeddings.
提出 LeakGauge，用行为后缀的 prefill 对数概率检测上下文泄露
Published Aug 18
Evaluated models Gemma-4-E4B-it , Gemma-4-31B-it , Qwen2.5-14B-Instruct and others11 提出嵌入推断攻击 EIA，在黑盒 IR 中识别所用嵌入模型
Published Jul 1
Evaluated models e5-small , e5-small-v2 , e5-base and others19 Abstract EIA 用无序文档集的差异从候选中识别嵌入模型，并给出 reranker 与阈值下的计数。EIA 是在黑盒 IR 上识别所用嵌入模型的攻击。 。
Propose soft prompt defense AREA, re-anchoring attention to mitigate system prompt leakage
Published Jun 17
Evaluated models Llama-2-7B-chat-hf , Llama-3.1-8B-Instruct , Mistral-7B-Instruct-v0.3 and others8 Abstract The authors measure commercial prompt leakage, propose attention drift, and use AREA to strike a trade-off between usability and leakage resistance.The authors study system prompt leakage in real LLM applications and propose AREA, a mitigation method that does not modify weights.
提出 MEntA，用非模板查询推断文档是否属于 RAG 检索库
Published May 23
Evaluated models Phi4-14B , Llama3.1-8B , CommandR-7B and others5 提出零知识审计协议，核验多租户 RAG 的合谋差分隐私
Published May 19 Abstract 揭示多租户 RAG 合谋泄露按根号 k 放大，提出带零知识证明的无泄露审计协议。论文针对多租户 RAG 服务在多账户协同攻击下隐私边界失效的问题展开研究。
建立 RAG 知识抽取攻防基准，统一评测抽取攻击与防御
Published Feb 10
Evaluated models GPT-4o , GPT-4o-mini , Llama3-8B-Instruct and others8 Abstract 统一基准比较 RAG 知识抽取攻防，作者称检索与生成都要优化，单一防御不能完全防护。作者给出一个比较 RAG 知识抽取攻击与防御的统一基准。
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