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Oct 12 · Monday

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  1. 研究者提出统一滥用监控基准,覆盖分解攻击与提示注入约 6200 条轨迹

    提出危害窗口与区间指标,统一评测分解攻击和提示注入下的智能体滥用监视

    Published
    Setting
    AI Agent
    Evaluated models
    Gemma 4 26B-A4B, Qwen3.6 27B, Qwen3.5 27B and others12

    Abstract统一智能体滥用监视框架,动作视角兼顾两类威胁但危害定位仍存瓶颈。

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  2. CART:面向大语言模型的闭环自适应红队框架

    提出闭环自适应红队框架 CART,评测模型与 Agent 的安全失败

    Published
    Setting
    AI Agent
    Evaluated models
    Claude Opus 4.8, GPT-5.5, Grok 4.3 and others7
    AbstractCART 把红队做成可审计的闭环搜索,在三类评测上比静态回放发现更多失败与更高平均风险。

    CART 把自动红队从一次清单式打分,改成带预算、可追溯的闭环搜索。

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  3. SafeScientist:让 LLM 智能体的科学发现具备风险意识

    提出 SafeScientist 四层监控,阻止科研智能体执行高风险或不伦理任务

    Published
    Evaluated models
    GPT-4o, GPT-4.1, GPT-3.5-turbo and others5
    Abstract四层监控加科研安全基准。

    SafeScientist 是带四层监控的科研智能体框架,并用 SciSafetyBench 评测科学场景中的任务安全。

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