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Oct 12 · Monday

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Harmful content5Output manipulation6Availability and reliability1Oversight failure5Increased misuse capability0

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Model layer1Training and data layer5
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Impact：Availability and reliabilityImpact：Increased misuse capabilityLayer：Model layerClear all

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  1. Analysis and theoryarXiv 2601.08668

    分析大语言模型在仇恨言论去毒中误拒行为的偏差

    分析 LLM 仇恨言论解毒误拒的群体偏差并测试跨语翻译缓解

    arXiv
    2601.08668
    Published
    Layer
    Model layer
    Setting
    Models and APIs
    Evaluated models
    GPT-4o mini, GPT-3.5 turbo, Llama-3.1 8B and others9
    Abstract九个 LLM 在解毒任务上普遍误拒，国籍宗教政治类偏高。

    作者考察对齐后的 LLM 是否会拒绝可接受的仇恨言论解毒请求，并分析误拒是否随目标群体和语言变化。完全拒答与夹带说教的部分拒答都计入。设置是固定提示、九个 LLM、三个英文集和法德西中韩。

    Paper analysisRead analysis
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