Translation in progress Some entries still include text in the original language.
Oct 12 · Monday
Another 240 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.
提出 STCA，对驾驶视频 VLM 构造可迁移的时空对抗扰动
Published Oct 6
Evaluated models Video-LLaVA-7B , Qwen2.5-VL-7B , Dolphins 提出 SceneJail，利用视频情境上下文越狱视频多模态模型
Published Sep 30
Evaluated models Qwen2.5-VL-7B-Instruct , Qwen2.5-VL-32B-Instruct , Qwen3-VL-8B-Instruct and others8 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。
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