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Oct 12 · Monday
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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.
主张多模态安全评测应衡量可控性，并用 SAE 建立四轴画像
Published Oct 5
Evaluated models LlavaGuard-v1.2-7B-OV , Qwen3.5-9B Abstract 四轴画像把读出与选择性控制分开。作者主张多模态安全评测在行为分类之外，单独报告可控性画像，而不是把检测准确当成控制证据。
提出 Geodesic Unlearning，沿测地线编辑权重以提升缺模态鲁棒性
Published Oct 4
Evaluated models RoBERTa , ResNet50 , Qwen2.5-3B and others6 Abstract GU 用测地线子空间编辑应对部署时缺模态下降，并尽量保住全模态精度。这项工作讨论多模态模型在部署时整段缺一个模态的性能下降，并把校正写成训练后的子空间编辑。
提出 Patch-to-Prune，旁路 VLM 部分层的视觉投影计算
Published Oct 2
Evaluated models Qwen2.5-VL-3B-Instruct , Qwen2.5-VL-7B-Instruct , LLaVA-v1.6-Vicuna-7B-HF and others4 Abstract P2P 用深度上的激活修补旁路视觉投影，以可调容忍度交换准确率与计算量。P2P 是面向 VLM 推理的训练无关计算旁路：不删除视觉 token，而在选定 decoder 层用固定激活代理代替视觉投影。
提出 WebFovea，加固视觉网页智能体的解析、执行、反馈与观察往返
Published Oct 2
Evaluated models claude-opus-4-6 综述视频生成的后训练与对齐，并汇总基准与开放挑战
Published Oct 1 Abstract 综述把视频后训练分成四类对齐信号，并指出奖励、长视频、权衡和安全仍开放。这是一篇视频生成 后训练与对齐 综述：预训练模型已有强先验，但作者认为仍不能可靠遵循意图、维持时间连贯或满足物理与安全约束。
研究视觉语言模型在协作中能否表示并说出指称不确定性
Published Sep 30
Evaluated models GPT-4.1 (2025-04-14) , GPT-5 (2025-08-07) , GPT-5.5 (2026-04-24) Abstract 指称不确定性可被引出，但很少说出来。
形式化视频透视头显中系统截图与人眼视野的错配
Published Sep 24
Evaluated models GPT-5.4 综述视觉内容全生命周期中的所有者侧对抗防护方法
Published Aug 5 Abstract 综述把五类对抗式保护收成一个生命周期，并用三条轴比较其主张。Adversarial attacks for good 是一篇视觉内容所有者侧保护的综述：把长期作为攻击来研究的扰动和结构化信号，反过来交给数据所有者、创作者、平台或审计方使用。
提出 FAIL 对抗模仿学习，对齐图像生成分布与专家演示
Published Feb 13
Evaluated models FLUX.1-dev , Xomni , Wan2.1-1.3B You have reached the end