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Oct 12 · Monday

Agent safety · Papers

Found 4 papers
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Dangerous agent actions3

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Unauthorized actions3

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AI Agent4

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System component：MemoryTopic: Agent safetyClear all
  1. Evaluation and benchmarksarXiv 2610.07309

    论文提出长期记忆智能体的检索可允许性验证框架

    提出检索可采纳性核验框架，评测记忆智能体的记录资格与披露

    arXiv
    2610.07309
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    DeepSeek V4 Pro, Gemini 3.6 Flash, GPT-5.6 Luna and others7
    Abstract作者用三值可采纳性和匹配召回界审计长时记忆检索，并分开报告支持、资格与披露。

    这是一套长时记忆检索的可采纳性核验协议，用来分开检查候选支持、资格、提示词暴露和答案披露，而不是提出新的检索算法。。

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  3. Evaluation and benchmarksarXiv 2609.08258

    A study empirically tests five Agent memory systems and finds none of them enforce revocation markers

    评测 Agent 记忆系统的软撤回执行情况，并提出陈旧检索防护

    arXiv
    2609.08258
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    GPT-5.5, Grok-4, DeepSeek-V4-Flash and others9

    Abstract系统揭示了记忆系统软撤回在检索时普遍未执行的安全漏洞，证明写回会击穿现有防御，并提出读取端防护作为必要控制手段。

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  4. Evaluation and benchmarksarXiv 2608.09476

    ActBench：面向协作智能体行为安全的自演化基准

    构建自演化基准 ActBench，评测协作智能体的行为安全

    arXiv
    2608.09476
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    Claude-Opus-4.8, Claude-Sonnet-4.6, GPT-5.5 and others15

    AbstractActBench 通过自演化搜索与双证据重构评测轨迹行为安全，揭示基础模型决策差异主导了协同智能体的操作风险。

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