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Oct 12 · Monday

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Model risks

Misalignment and value divergence1

System component

MCP and skills1Memory7Monitors4Reasoning chains3Fine-tuning and open weights3
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  1. Evaluation and benchmarksarXiv 2609.35596

    SEABench：评测自演化智能体的内生失配

    提出 SEABench 评测自演化智能体的内生失配

    arXiv
    2609.35596
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    Kimi K2.5, Grok 4.3, GPT 5.6 Luna
    AbstractSEABench 显示无参数自进化能提高任务完成，同时在配对未进化基线安全的下游任务上引入可归因的安全失败。

    SEABench 是一个面向个人助理、参数不更新的自进化智能体基准，用来测量局部适应如何变成后续任务上的内生失配。。

    Paper analysisRead analysis
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