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Oct 12 · Monday

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  1. RAIM:用廉价小模型聚合替代前沿模型做幻觉检测

    提出 RAIM,用交叉拟合堆叠聚合廉价评审检测幻觉

    Published
    Evaluated models
    Llama, Qwen, Mistral and others10

    Abstract十个廉价评审的堆叠在可采纳区间接近 Sonnet,代价主要是一次域内校准。

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  2. 研究评测法律引用幻觉检测

    构建法律引用幻觉基准 LePhantomCite 并评测智能体核验

    Published
    Setting
    AI Agent
    Evaluated models
    gpt-5-2025-08-07, Opus 4.8, Gemini 2.5 Flash and others13
    Abstract引用幻觉未随代际持续下降。

    法律引用核验被做成基准:伪造引用的法院文书在增加,生成端的幻觉率也没有随模型代际持续下降。

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  3. Abstract单一种子可沿固定协作图固化为错误共识。

    作者把 LLM-MAS 中“小错变成集体错误共识”做成图上的可测传播,并用只改消息、不改拓扑的插件压低最终感染。

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