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Oct 12 · Monday

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  1. DefensesarXiv 2609.39548

    NDDL:用正常扩散动力学为文生图模型做后门防御

    提出 NDDL,用良性扩散轨迹检测文生图后门提示并定位触发 token

    Published
    Evaluated models
    Stable Diffusion v1.5, Stable Diffusion XL, Stable Diffusion v3.5 and others4
    AbstractNDDL 从良性扩散轨迹学习正常转移,用动态不一致检测后门并定位触发 token。

    NDDL 是面向文生图扩散模型的后门防御:防御者只有白盒模型访问和良性提示词,没有后门先验,需要区分后门提示词并找出触发 token。

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  2. FAME:用反事实推理评测自主智能体的虚假记忆

    提出 FAME,用反事实概念漂移评测智能体虚假记忆

    Published
    Evaluated models
    Llama-3B
    AbstractFAME 用反事实引起的隐状态概念漂移,在出答案前区分忠实记忆与虚假记忆。

    FAME 是一个免训练的评测框架,用来判断自主智能体的记忆在虚假相关、环境偏移或知识冲突下是否已变成虚假记忆。。

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  3. DefensesarXiv 2610.00348

    NEEDLE:通过权重正交化移除 LLM 后门

    提出 NEEDLE,用权重正交化在已知触发器时去除大模型后门

    Published
    Evaluated models
    Gemma-3-4B-IT, Qwen3-4B-Instruct-2507, Gemma-3-12B-IT

    AbstractNEEDLE 用闭式权重编辑去掉已知触发器的后门,并保住拒绝子空间。

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  4. DefensesarXiv 2607.14737

    GeoDetect:面向视觉语言预训练模型的几何对抗检测方法

    提出 GeoDetect 以几何分数检测视觉语言预训练模型的对抗样本

    Published
    Attacker
    White-box
    Evaluated models
    CLIPViT (ViT-B/16), CLIPCNN (ResNet-50), ALBEF and others4
    AbstractGeoDetect 用几何分数检测 VLP 对抗样本。

    GeoDetect 是面向视觉-语言预训练模型的对抗样本检测方法,用嵌入几何而不是任务 logits 区分干净样本与对抗样本。

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  5. DefensesarXiv 2602.03085

    Triggers in the Haystack: Extracting and Reconstructing LLM Backdoor Triggers

    提出推理扫描器,在仅有模型文件时检测后门并重构触发词

    Published
    Evaluated models
    gemma-3-270m-it, DeepSeek-R1-Distill-Qwen-1.5B, Phi-4-mini-instruct and others8
    Abstract用记忆泄漏和内部信号重构触发词。

    这是一个只做推理的 sleeper agent 扫描器:在不知触发词和目标行为时,检测因果语言模型里的条件后门并重构触发词。。问题在于,后门只在触发词出现时偏离基线,而开放仓库和网页投毒使检测方通常没有触发词、目标或激活语料。

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