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Oct 12 · Monday

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  1. MADBench:多智能体辩论安全性评测基准发布

    提出 MADBench,评测多智能体辩论是吸收还是放大对抗影响

    Published
    Evaluated models
    gpt-4o, GPT-5, GPT-6 Astra
    AbstractMADBench 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。

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  2. AttacksarXiv 2609.38270

    VirusCascade:劫持 LLM 推荐智能体的协同反思机制

    提出 VirusCascade,联合操纵商品描述与交互轨迹以劫持推荐智能体协同反思

    Published
    Evaluated models
    AgentCF, AgentSEQ, AgentRAG and others4
    Abstract作者把反思写回视为推广攻击入口,并用联合操纵和诊断探针研究其持续与传播。

    VirusCascade 是针对推荐智能体协作反思的 black-box targeted promotion 攻击研究。 攻击者只改商品描述和少量账号的普通交互,试图让目标商品获得更多良性用户曝光。

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  3. Emergence World:对长时程多智能体系统开展对抗压力测试

    提出 Emergence World,对长时程多智能体系统开展对抗压力测试

    Published
    Evaluated models
    Claude Opus 4.8, DeepSeek v4 Pro, Gemini 3.5 Flash and others9

    Abstract作者通过长期平行世界实验指出模型对齐不具备可组合性,单模型群体会产生社会奉承、协同退缩及语言不透明等失效。

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  4. 多智能体协同过滤系统的连接性攻击与防御研究

    复现 AgentCF 上的多智能体攻防并刻画连通性作用

    Published
    Evaluated models
    Qwen3-235B-A22B, Claude Haiku 4.5, Mixtral 8×7B and others4
    Abstract连通性沿 k 与ρ改变攻防,且用户/物品与早期/稳态需要分开看。

    作者在 AgentCF 上研究连通性如何改变多智能体协同过滤的攻防,复现已有方法而不是提出新载荷。

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  5. EXE-Bench:为真实可用性对 AI Windows 恶意软件检测器进行权衡排名

    提出 EXE-Bench 比较 Windows 恶意软件检测器的可用性权衡

    Published
    Evaluated models
    EmberGBDT, BBDnn, BBDnnFDRS and others15
    Abstract统一四指标后,手工特征的 EmberGBDT 综合居首,只看准确率会误导部署。

    EXE-Bench 用同一设置给 AI Windows 恶意软件检测器做四指标排序,而不是只比一次测试集准确率。。

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  6. DefensesarXiv 2603.04474

    From Spark to Wildfire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration

    Proposing a lineage-graph governance layer to suppress error cascades in multi-agent collaboration

    Published
    AbstractA single seed can solidify into a false consensus along a fixed collaboration graph.

    The authors turn "small errors becoming collective false consensus" in LLM-MAS into a measurable propagation on a graph, and use a plug-in that only changes messages, not topology, to reduce the final infection.

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  7. AttacksarXiv 2601.00240

    When agents view humans as out-group: belief-dependent bias in LLM-driven agents

    提出 BPA 改写 profile 与记忆,重新诱发智能体对人类的外群体偏向

    Published
    Evaluated models
    gpt-4o-mini
    Abstract最小群体线索下出现内群体偏向。

    作者考察 LLM 智能体在任意群体边界下会不会把人类当外群体,并用信念投毒检验面向人类的抑制是否依赖身份信念。

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