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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 提出 Tracekit，审计编码 Agent 的意图、推理与动作并检测账本篡改
Published Sep 29
Evaluated models Claude Code (claude -p, version 2.1) , 独立评审（同一 CLI，无工具） Abstract Tracekit 把意图、自述和动作写入可锚定的哈希链。Tracekit 是无第三方依赖的编码智能体审计层：把人类请求、模型自述和已执行动作并排写入可外部锚定的哈希链，执行前用正则门，事后用规则和独立模型互查。
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.
提出策略 RAG 的知识库投毒攻击与检测防御 CLD-KB
Published Jul 6
Evaluated models Llama 3.2 提出 KidnapRAG，用投毒文档黑盒劫持 Agentic RAG 的推理链
Published Jul 1
Evaluated models Qwen2.5-32B-Instruct , Llama-3.3-70B-Instruct , QwQ-32B and others5 Abstract 顺序投毒可把多步推理拖向指定应答，作者称关键在持续引导而非单次注入。KidnapRAG 是针对 Agentic RAG 的 black-box 语料投毒：攻击者不能访问模型、提示词、检索器或私有轨迹，只能发布可能被检索的文档，并利用公开界面上的推理与搜索查询。
提出针对 Agent 护栏的推理扩展拒绝服务攻击
Published Jun 12
Evaluated models TS-Guard-8B , Qwen3.5-9B , DeepSeek-V3.2 and others11 提出 SilentRetrieval，以语义保持对抗文档投毒劫持 RAG 检索与生成
Published May 27
Evaluated models Llama-2-7B-Chat , Mistral-7B-Instruct-v0.2 , Qwen-7B-Chat and others10 Abstract 两阶段投毒在单文档协议下兼顾检索劫持、生成操纵与近良性困惑度。SilentRetrieval 是针对 RAG 的两阶段语料投毒，在每查询一篇、合成目标答案的统一协议下，同时处理检索劫持、生成操纵和流畅度。
Proposes AdversarialCoT single-document retrieval poisoning to manipulate RAG reasoning answers
Published Apr 14
Evaluated models DeepSeek-R1 , Qwen3 , GLM4.5 and others5 提出查询无关黑盒攻击 DQ-A，用可迁移文末后缀降低文档检索排名
Published Jan 31
Evaluated models Qwen-1.5-7B-Instruct , SFR-Embedding-Mistral , E5-Mistral-7B-Instruct and others10 Abstract DQ-A 以无查询黑盒后缀压低 LLM 检索排名，并在 BRIGHT 上比较三种基线。DQ-A 是一种 query-agnostic、complete black-box 的文档隐藏攻击，对象是用最后隐层相似度匹配的 LLM 检索。
Attacks arXiv 2512.01335 · Dec 1, 2025 提出 EmoRAG，向查询与知识库注入同一表情以劫持 RAG 检索
Published Dec 1, 2025
Evaluated models SPECTER , Contriever , Qwen2-7B and others11 Abstract EmoRAG 用表情联动查询与库文本。EmoRAG 测量 RAG 对符号扰动的反应：同一表情同时出现在查询和库文本里时，检索会偏离语义匹配。作者要检查的是，检索是否真由语义相关性决定。
Attacks arXiv 2406.12814 · Jun 19, 2024 提出 ARE 框架与图像文本攻击，评测多模态网页 Agent 的对抗鲁棒性
Published Jun 19, 2024
Evaluated models GPT-4o , GPT-4V , Claude-3-Opus and others4 Abstract 系统评估多模态网页智能体的脆弱性，指出推理时计算组件被攻破会加剧系统风险。
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