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Oct 12 · Monday
All papers Found 13 papers Another 254 papers do not have category tags yet and are not included in filtered results.
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About this collection Collection in progress We are building a large AI safety paper collection to help researchers find work related to their interests. Papers are collected automatically andfiltered only for relevance to AI safety , without judging quality, novelty or reading value. The default “Annotated first” shows papers with tags or published paper analyses first. Each group is ordered by original publication date, newest first, with undated papers last. “Newest first” uses publication dates only. This order is not a quality ranking.
One-line summaries, tags and paper analyses are prepared by AI from the papers. Language models may have systematic biases and produce hallucinations.We plan to carry out human annotation and review to reduce errors in this content.
Propose KVeil, which adds perturbations to face videos to prevent unauthorized customization from reproducing identity
Published Oct 9
Evaluated models Wan2.2-TI2V-5B , HunyuanVideo-1.5 , Kling 3.0 and others4 Abstract KVeil adapts LETHE's reference-reading disruption to the challenge's two stages, ranking first on the leaderboard in both Final columns.
提出 OrthoPurify，用正交投影清除视觉语言模型适配器中的劫持方向
Published Oct 7
Evaluated models LLaVA-1.5-7B , Qwen3-VL-8B , LLaVA-1.5-13B and others5 Abstract 一次投影去掉劫持方向。OrthoPurify 是部署前的 LVLM 后门净化方法，用一次正交投影去掉被劫持的权重更新方向。
提出 BadAction，通过动作触发器给交互式视频生成植入后门
Published Sep 30
Evaluated models Astra (Wan2.1-T2V-1.3B)
Published Sep 28
Evaluated models E-Branchformer Abstract 梯度上升类方法更接近简单评测下的重训参照，复杂方法会被知情攻击认出，多说话人更差。
提出 ODPure，在输入阶段用腐蚀重建与共识净化目标检测后门
Published Sep 23
Evaluated models YOLOv5 , Faster R-CNN 提出 FreqDoor，在频域混合振幅并对生成式 VLM 做训练时视觉后门
Published Sep 7
Evaluated models BLIP-2 (opt-2.7b) , InstructBLIP (flan-t5-xl) , LLaVA (interleave-qwen) Abstract FreqDoor 用频域振幅混合给三款 VLM 植入仅视觉的训练时后门。FreqDoor 是针对生成式 VLM 的仅视觉、训练时后门：在频域混合触发源振幅、保留干净图像相位，使触发在空间上分散。
提出持续学习下的净化与选择性恢复框架，抵御逐任务训练投毒后门
Published Sep 6
Evaluated models ViT-B/16 Abstract 作者报告任务内净化与恢复可配合动态专家防御后门，但保证依赖分离条件。这是一项面向持续图像分类的后门防御研究 ：模型只使用当前任务数据，同时需要保留过去知识并避免学习恶意监督。
提出 TRIM，在黑盒推理时定位并净化图像后门区域
Published Sep 3
Evaluated models ResNet-50 提出 GhostWord 词级触发后门，对自动语音识别做数据投毒
Published Sep 2
Evaluated models Whisper-Small , Whisper-Medium , MMS and others4 提出 RACER，用区域感知一致性对抗微调去除多模态大模型后门
Published Aug 25
Evaluated models LLaVA-1.5-7B , Qwen2-VL-7B , Qwen2.5-VL-7B 提出 TC-UAP，用身份级多帧扰动保护视频免被定制复现身份
Published Jul 15
Evaluated models LTX-2.3 , Wan2.2-5B Abstract TC-UAP 以可复用的时间一致扰动干扰两类定制共用的 VAE 隐空间。作者要解决的是：发布前如何给视频加不可见扰动，使片段既不能被拿去微调视频扩散模型，也不能被抽帧做 image-to-video。
提出 VPH 与 VTH，只改视频帧劫持世界模型并投毒下游策略
Published Jun 8
Evaluated models Cosmos-Predict 2.5 , Cosmos-Predict 2.5 AC , Dino WM and others4 Abstract 只改视频帧经世界模型投毒。只改看似安全的视频帧，经世界模型之后才改变下游机器人策略。 问题在于世界模型进入数据生成后，数据集检查看到的仍是安全演示，合成轨迹却可以变危险。
提出 BackdoorVLM 基准，评测视觉语言模型微调中的后门攻击与防御
Published Nov 24, 2025
Evaluated models LLaVA-1.5-7B , Qwen2.5-VL-7B Abstract BackdoorVLM 统一评测 VLM 后门与防御：含文本触发在低投毒率下更易激活，现有防御跨类型不稳定。BackdoorVLM 是作者提出的 VLM 后门攻击与防御评测基准，作者称它是首个此类综合基准。
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