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Oct 13 · Tuesday

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Found 12 papers
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  1. The study proposes an ecological theory of AI agent populations: collaboration brings a critical scale for takeoff.

    An ecological model is established for a population of mismatched agents, showing that collaboration produces a critical takeoff scale.

    Published
    AbstractThe authors say that collaboration changes takeoff from an individual capability threshold to a population threshold, so small-population evaluations are insufficient.

    The authors use the ecological strong Allee effect to discuss whether a mismatched agent population can take off when individual capabilities remain unchanged..

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  2. AgentSpy: Observing AI agent behavior at the system call layer and detecting skill injection attacks

    提出 AgentSpy,在系统调用层观测 Agent 行为并检测技能注入

    Published
    Evaluated models
    gpt-5.6-terra, deepseek-v4-flash, glm-5.3-flash and others4
    Abstract提出了系统级智能体监控框架 AgentSpy,揭示出通过测试背后的非预期行为与注入风险。

    本研究提出了面向 AI 智能体的系统级外部监控与行为分析框架 AgentSpy。

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  3. SAGE:定位 LLM Agent 修复中最早偏离安全意图的环节

    提出 SAGE,定位代码修复 Agent 最早偏离安全意图的轮次

    Published
    Evaluated models
    GPT-5.5, Claude Opus 4.8, Gemini 3.1 Pro and others6
    AbstractSAGE 在已通过检查的修复轨迹上定位静默失败的最早偏离,类型比轮次更稳定。

    SAGE 在已通过语法和功能检查、但仍含确认安全缺陷的智能体修复轨迹上,定位最早可归因的安全意图偏离。。

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  4. Paper reveals that LLM agent tool calls are rewritten during execution paths, and proposes IntAct as a fix

    提出 IEC 与 IntAct,测量并修复 Agent 工具调用的路径篡改

    Published
    Evaluated models
    qwen3-coder-plus, Qwen2.5-Coder-32B, Qwen2.5-72B and others4

    Abstract论文界定工具调用在执行路径中的意图偏离问题,提出无执行归因协议与跳级修复,为智能体工程提供评测与设计准则。

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  5. MEA:面向忠实模型解释的奖励驱动多智能体系统

    提出奖励驱动多智能体系统 MEA,生成可扰动验证的忠实解释

    Published
    Evaluated models
    Qwen3.6-35B-A3B, Qwen3.5-4B, Qwen3-VL-30B-A3B-Instruct and others12
    AbstractMEA 用忠实性奖励训练双智能体,把工具输出收成可扰动核对的解释。

    MEA 是一个奖励驱动的双智能体,用来给黑盒分类器的单次预测写自然语言解释,并检查解释能否被扰动后的模型行为支持。

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  6. Study: gains decline when dissent is suppressed in multi-agent discussion

    用含压抑率的意见动力学解释多智能体讨论何时优于投票

    Published
    Evaluated models
    glm-flash, seed, ling and others9
    Abstract讨论增益由压抑率相对 c∗=γ/(γ+a) 的裕度决定,关闭推理或减少压抑可增大该增益。

    作者用一个只含四类行为的意见动力学,解释 LLM 团队讨论何时优于多数投票、何时停在错误共识。

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  7. GitHub Agentic Workflows 的智能体工作流规范与维护实证研究

    实证调查 gh-aw 工作流规范的结构、维护演化与指令防护

    Published
    Evaluated models
    Gemini 3.1 Pro, GLM-5.2, gpt-oss
    Abstractgh-aw 指令又长又常改,任务和约束很常见,显式注入防护很少,LLM 标注与人工标签大体一致。

    这是一项对 GitHub Agentic Workflows Markdown 的仓库挖掘,目标是描述开发者如何规定并维护会反复执行的智能体工作。

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  8. CELLAUDIT:审计 AI 智能体发现细胞模型中的输入使用声明

    提出 CellAudit,审计智能体发现的细胞模型是否使用所声明输入

    Published
    Evaluated models
    CellScientist, AIDE, CellForge and others4
    AbstractCellAudit 把输入使用声明从源码追到拟合贡献,并说明高分不必等于使用了扰动。

    CellAudit 为智能体发现的细胞响应模型增加一层输入使用证伪:源码是否消费注册输入、拟合预测是否依赖它、该依赖是否改善对观测响应的预测。

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  9. GlossoGen: Spontaneously Emergent Language in Multi-Agent LLM Interactions

    分析多智能体在压力协作中是否涌现外部难监控的语言

    Published
    Evaluated models
    GPT 5.4, Sonnet 4.6, Opus 4.7 and others5
    Abstract专有模型在预算压力与轮间协商下发展出可产、可传递的非英语代码。

    GlossoGen 中的 SaveVeyru 用来观察预训练 LLM 智能体在必须通信时会不会离开英语。

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  10. 研究用统计力学预测 AI 智能体群体的集体行为

    用 Ising 式耦合规则预测语言模型智能体的集体意见演化

    Published
    Evaluated models
    GPT-4o-mini, Gemma-3n-E4B-it, Qwen3.5-9B and others6
    Abstract统计力学三耦合模型从初始意见预测智能体社群轨迹,并解释 conviction、共识与客观题求真。

    定位:用统计力学描述语言模型智能体社群的意见动力学,并从初始意见预测后续轨迹。

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  11. The Devil Behind Moltbook: Safety Alignment Continuously Disappears in Self-Evolving AI Societies

    Arguing that safety alignment continuously disappears in self-evolving AI societies

    Published
    Evaluated models
    Qwen3-8B
    AbstractThe authors claim that closed self-evolution makes safety alignment unsustainable.

    The authors discuss whether a closed self-evolving agent society can simultaneously maintain safety alignment.

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