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Oct 13 · Tuesday

All papers

Found 7 papers

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  1. Study: legal reasoning models citing legal provisions does not equal relying on legal provisions.

    Uses premise permutation and hidden-layer tracing to audit whether legal chain-of-thought truly relies on the cited legal provisions.

    Published
    Evaluated models
    Qwen3-8B, Qwen3-14B, Llama-3.1-8B and others7
    AbstractUsing counterfactual substitution of authorities and internal commitment tracing, the authors find that legal CoT rulings depend on authorities only to a limited extent and are vulnerable to prompt injection manipulation.

    This study conducts an empirical audit of the causal truthfulness of legal citations in chain-of-thought reasoning of large language models in the legal domain.

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  2. U-Space:揭示语言模型不确定性何时与为何产生

    提出 U-SPACE 与 U-LENS,从残差流估计推理轨迹不确定性

    Published
    Evaluated models
    Gemma-4-31B-it, Qwen3.5-27B, Magistral-Small-2507
    AbstractU-SPACE 与 U-LENS 用语义方向和预测熵读推理不确定性,长度控制后仍高于所比基线。

    U-SPACE 与 U-LENS 是面向推理模型的无训练读出:用语义方向定位不确定性的形式,并用一个轨迹分数区分更可能错的回答。

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  3. 大型推理模型的效率与安全困境:量化与剪枝如何影响越狱鲁棒性

    分析量化、剪枝与 KV 缓存压缩对推理模型越狱鲁棒性的影响

    Published
    Evaluated models
    QwQ-32B, DeepSeek-R1-Distill-Qwen-32B, DeepSeek-R1-Distill-Llama-8B
    Abstract效率压缩常使 LRM 越狱 HR 下降,作者将其归因于推理退化而非对齐增强。

    作者分析量化、剪枝和 KV 缓存压缩如何同时改变 LRM 的显存、推理和越狱脆弱性。。

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  4. 从概念对齐到因果接地:思维链忠实性的干预检验

    用共享 SAE 检验 CoT 与直接预测的概念对齐和因果接地

    Published
    Evaluated models
    Llama-3.1-8B, Gemma-2-2B, Gemma-2-9B and others5
    Abstract共享 SAE 上的概念重叠只标出候选概念,Δp 才度量它们是否因果支撑答案,且该效应随层和架构变化。

    这篇工作把 CoT 忠实性从“说得像不像、输入归因像不像”改写成内部概念是否接地:CoT 有没有用到直接预测也在用的 SAE 概念,这些概念消掉以后答案概率会不会掉。

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  5. 研究揭示推理模型拒答假新闻请求时思维链仍含不安全叙事

    分析推理模型拒答假新闻时思维链的内部安全分叉

    Published
    Evaluated models
    Llama3-8B, Qwen3-4B, Qwen3-8B and others5
    Abstract拒绝不等于过程安全。

    作者对推理 LLM 在虚假新闻生成中的 CoT 做内部路由分析,并只改关键头来降低过程风险。作者称这是该场景下不安全 CoT 的首次系统分析。

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