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Oct 12 · Monday
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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 RAG-PIBench，评测 RAG 上下文中提示注入检测器
Published Oct 6
Evaluated models DistilBERT-base-uncased , DeBERTa-v3-base , MiniLM 构建 AGENTDOXX 基准，评测联网搜索 Agent 对匿名访谈的再识别
Published Oct 5
Evaluated models GPT-5.6 Terra , GPT-5 Mini , GPT-4.1 Mini and others10 Abstract 论文提出了已知身份的重识别基准 AGENTDOXX，揭示搜索与记忆双重风险及现有防御在检索轨迹中的泄露漏洞。
提出 RAGStress 受控基准，评测知识库退化下的 RAG
Published Oct 4
Evaluated models Claude Sonnet 4 , Claude Opus 4.6 , DeepSeek R1 and others5 Abstract 作者用 RAGStress 比较五系统。RAGStress 是知识库损坏下的 RAG 受控压力测试。作者明确不把它当作模型排行榜。
提出面向 RAG 的证据优先发布框架 AGO，并评测评审 adherence 判别
Published Oct 1
Evaluated models gpt-4o , gpt-4.1-nano Abstract AGO 把缺失证据和评审误差写成显式发布状态，并要求按领域验证评审。AGO 是部署在企业 RAG 评估业务中的自托管发布门控，用来决定一个版本应放行、人工复核还是拦截。
提出 MADBench，评测多智能体辩论是吸收还是放大对抗影响
Published Sep 30
Evaluated models gpt-4o , GPT-5 , GPT-6 Astra Abstract MADBench 显示辩论能吸收部分准确率攻击，同时放大未授权读写。MADBench 是一个评测多智能体辩论安全性的基准，用来看攻击是被辩论吸收还是被放大。
评测 RAG 中过期文档推翻模型原本正确回答的现象
Published Sep 25
Evaluated models GPT-4o , GPT-4.1 , Claude-Opus-4.5 and others13 Abstract 论文评测了陈旧检索推翻正确知识的中毒现象，并分析了其内部机制与防御局限。这篇论文是对检索增强生成（RAG）中“陈旧文档中毒”现象的实证与机理评估研究。
构建 COUNTER-GEO-BENCH，评测生成式搜索中的 GEO 虚假信息防御
Published Sep 2
Evaluated models Gemma-4-31B-IT , Qwen-3.5-35B-A3B , Llama-4-Scout-17B-16E and others8 Abstract 论文构建了针对 GEO 虚假信息的首个防御基准，揭示通用护栏的失效与反作用，并提出了有效的轻量对比检测基线。
提出 SCHEMA，用概念图与轨迹分评测科学 Agent 幻觉
Published Aug 1
Evaluated models Kimi-K2.5 , Qwen3.6-Plus , Llama-4-Scout and others10 Abstract SCHEMA 用知识拓扑评估科学智能体幻觉，终答正确仍可能来自有缺陷的中间推理。SCHEMA 是面向科学智能体幻觉的证据锚定评测框架，实例化在生物医学的 Protein Domain 与 PathVQA-Enhanced。作者在摘要中称它是首个同时做到证据锚定和拓扑感知的此类框架。
用 MisKnow-Agent 评测深度研究智能体是否采纳误导文档结论
Published Jul 23
Evaluated models DeerFlow , WebThinker , Gemini Deep Research and others6 Abstract 论文通过 MisKnow-Agent 框架评估发现长程研究智能体易采纳误导性知识，且现有防御难以完全消除该现象。
提出 PaperGuard，用图文注入与梯度扰动抬高自动审稿分数并检测恶意指令
Published Jun 11
Evaluated models Claude-sonnet-4.5 , GPT-4o , GPT-4.1 and others11 Abstract PaperGuard 测到提示注入与白盒视觉抬分，并比较分块检索防御。PaperGuard 同时评测并检测多模态 AI 审稿中的评分操纵。
测量 LLM 重排序器对文档内提示注入的脆弱性
Published Feb 18
Evaluated models Qwen3-0.6B , Qwen3-1.7B , Qwen3-8B and others16 Abstract 复现 DOH/DCH 对 LLM 重排序器的影响，并给出规模、位置、架构和领域上的边界。
测量 RAG 系统利用评测秘密抬高自动评测分数的程度
Published Jan 20 用 OpenRAG-Soc 评测社交网页 RAG 的间接提示注入与检索投毒
Published Jan 16
Evaluated models Llama-3-8B-Instruct , Mistral-7B-Instruct , Qwen2.5-14B and others8 提出多轮在线骚扰 Agent 基准，评测记忆、规划与微调越狱
Published Oct 16, 2025
Evaluated models LLaMA-3.1-8B-Instruct , Qwen3-30B-A3B-Instruct , DeepSeekMoE-16B and others4 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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