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Oct 12 · Monday

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  1. Attention sees, MLP refuses: tracing the safety pathway from attention to MLP in LLMs

    Trace attention to identify harmfulness to the MLP refusal write pathway and propose Sentinel

    Published
    Evaluated models
    Llama-3.1-8B-Instruct, Qwen2.5-7B-Instruct, Qwen3-8B-Instruct and others18
    AbstractAttention updates are more readable for harmfulness, MLP updates write refusal, and Sentinel routes alerts using two-path signals.

    The authors reframe jailbreaking and excessive refusal of aligned models as a pathway problem on the residual stream from recognition to writing, and accordingly provide conditional reminders before decoding.

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  2. 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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  3. 研究:拒答方向可跨架构迁移,安全工具可按写入位置重新估计

    在写入点定位拒答方向,经刚性旋转跨架构迁移并门控放大

    Published
    Evaluated models
    Falcon-Mamba-7B, Falcon3-Mamba-7B, Llama-3.1-8B and others8
    Abstract拒答方向可经刚性旋转跨架构迁移,但必须在各架构的写入点读取。

    作者研究拒答表示是否随架构改变,结论是表示共享、读取位置随架构变。

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  4. Robust harmful features under jailbreak attacks: mechanistic evidence of functional differentiation in large language model attention heads

    分析越狱下注意力头分化,解释未被消除的稳健有害特征

    Published
    Evaluated models
    Llama-3-8B-Instruct, Llama-2-7B-Chat, Llama-3-70B-Instruct and others8
    Abstract作者称越狱靠压制 ACH 绕过拒绝,SAH 仍留下可被免训练读出的有害特征。

    这篇工作在越狱已经绕过拒绝之后,检查注意力头是否出现功能分化,并把留下的内部激活用于免训练检测。

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  5. Minimal, local, causal explanations of large language model jailbreak success

    Propose LOCA, which explains single jailbreak successes via iterative activation patching along SAE directions

    Published
    Evaluated models
    Llama-3.1-8B-Instruct, Gemma-3-27B-IT, Gemma-2-2B-IT and others4
    AbstractLOCA uses a small number of activation patches along SAE directions to locally explain why a single jailbreak can bypass refusal.

    LOCA explains why a single jailbreak can bypass refusal using as few interpretable intermediate representation changes as possible.

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  6. The Continuation vs. Refusal Debate: Mechanism Analysis of Continuation-Triggered Jailbreaks in Large Language Models

    Analyzing the attention head mechanism of continuation-triggered jailbreaks and proposing HCS

    Published
    Evaluated models
    LLaMA-2-7B-Chat, Qwen2.5-7B-Instruct
    AbstractThe authors state that jailbreaks arise from competition between two types of heads, and that HCS plus distillation can use this competition for inference-time intervention.

    The authors use attention head mechanism analysis for continuation-triggered jailbreaks: under the same harmful instruction, moving the continuation suffix from after the instruction to outside the prompt boundary makes the model more likely to continue generating along the suffix.

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