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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.
提出多智能体系统提示注入的威胁模型与四层架构防御
Published Sep 19
Evaluated models GPT-4o (2024-08-06) , Claude 3.5 Sonnet , Llama 3 70B-Instruct 用任务绑定令牌和策略预言机拦住多智能体流水线的未授权执行
Published Sep 15
Evaluated models gemma4:31b-cloud Abstract 结构性授权拦住了记忆投毒的未授权执行,持密钥时承重的是策略预言机。作者在一条会改写沙箱邮件库的四智能体流水线上,检查低权限失陷会不会变成未授权的真实动作。
提出 k-robust 联盟对齐,刻画误对齐评审下的安全委托授权
Published Sep 15 Abstract 联盟覆盖使无个体对齐的评审面板仍可相对基线安全授权,数值分数改善完备性。委托授权的安全不要求每位评审者对齐,而要求面板在效用空间覆盖委托人。
提出 MasDrift,评测多智能体在良性任务中的授权保持
Published Aug 2
Evaluated models DeepSeek V4 Flash , Qwen3.7 Plus , GPT-5.4 Nano and others6 Abstract 授权保持可被测量:层级用未授权动作换完成率,重锚定比沿链携带更稳。MasDrift 把多智能体设计中的授权保持 做成可测量性质,对象是没有攻击者的普通委托。
建模并利用多智能体网络中子智能体生成时的记忆继承漏洞
Published May 9
Evaluated models MiniMax M2.5 , Llama-4-Maverick-17B-128E-Instruct-FP8 , Qwen3.5-Plus and others5 Abstract 形式化子智能体继承,在 OpenClaw 上演示四类编排层漏洞并提出防御。作者对多智能体网络里的子智能体继承 做形式化分析,并用开源框架上的 PoC 演示编排层如何让单点妥协继续扩散。
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