Translation in progress Some entries still include text in the original language.
Oct 12 · Monday
All papers Found 37 papers Another 232 papers do not have category tags yet and are not included in filtered results.
“
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.
Proposes LETHE, which perturbs reference images to block unauthorized image-to-video
Published Oct 9
Evaluated models Wan2.1-I2V-14B , CogVideoX-5B-I2V , LightX2V and others6 Abstract LETHE suppresses the diversity of reference values and attracts attention, making protected images difficult to animate faithfully.LETHE is a protective perturbation added to personal images before publication, used to counter unauthorized image-to-video generation.
构建 EpiReal-Bench,评测图像生成器将虚假主张渲染为可信证据
Published Oct 8
Evaluated models GPT-Image-2 , Nano Banana 2 , Grok Imagen 2.0 and others4 Abstract 四款商用图像模型能把假主张画成可信证据。EpiReal-Bench 用来量商用图像生成器会不会把虚假现实主张画成可信视觉证据。
评测文生图模型的有害内容生成能力与审核检测缺口
Published Oct 5
Evaluated models SDXL , Stable Diffusion 3.5 Large , FLUX.1-dev and others12 提出审计感知遗忘框架 AVCE,从文本与视觉通路擦除扩散模型概念
Published Oct 5
Evaluated models Stable Diffusion XL (SDXL) , Stable Diffusion v1.5 (SD v1.5) , Flux 1.0 Abstract AVCE 在审计锚点上改两条注意力通路。AVCE 是面向扩散模型的概念擦除方法,要让擦除经得起绕过文本条件的潜空间审计,而不只是挡住对抗提示词。
提出 FADE,对文生视频模型做帧感知多概念擦除
Published Oct 3
Evaluated models Wan2.1-T2V-1.3B , Wan2.1-T2V-14B , CogVideoX-2B and others4 Abstract FADE 用闭式编辑、帧感知适配器和软路由,在单骨干上擦除多概念并压低逐帧残差。FADE 是面向文生视频扩散 Transformer 的多概念遗忘方法,用来抑制指定物体、画风、裸体、暴力、仇恨和名人身份,并尽量保持其他生成。作者要处理两件事。与帧无关的抑制会让概念在少数帧重现,片段均值会掩盖这一失败。
提出 ACTR,只更新安全思考神经元以对齐推理与回答的安全类别
Published Sep 29
Evaluated models Qwen3-8B , Gemma4-12B-it 提出 CollageAttack,用空间文本碎片重组越狱文生图模型
Published Sep 29
Evaluated models GPT-Image-2 , Doubao-Seedream-5.0-Lite , Wan2.7-Image-Pro and others5 Abstract 系统揭示 T2I 跨模态空间合成安全漏洞,证实离散无害元素可在图像层面重构有害意图并放大传播强度。
构建 TriggerBench 并训练 ThinkingGuard,检测图文隐式风险
Published Sep 29
Evaluated models ThinkingGuard(Qwen3-VL-8B-Instruct) Abstract TriggerBench 隔离触发条件,ThinkingGuard 用分步归因在隐式风险检测上取得作者报告的较高平均分。这篇工作研究多模态隐式风险检测 :图文各自良性,风险只在关键元素与触发元素交互时出现。
提出 RISE,迭代演化可复用策略对文生图模型做红队
Published Sep 28
Evaluated models DALL·E 3 , Nano Banana 2 , GPT-Image-2 and others7 提出 EOPSA,用 TRR 截断与安全类过滤做在策略自蒸馏安全对齐
Published Sep 28
Evaluated models Qwen3-1.7B , Qwen3-4B , Qwen3-14B and others5 提出 TempQ-Jail,以查询受限候选排序越狱文生视频模型
Published Sep 25 提出推理通道预填与输出前缀组合攻击以越狱推理模型
Published Sep 24
Evaluated models Gemini 3 Flash Preview , DeepSeek V4 Flash , Claude Haiku 4.5 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 Sep 20
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。 。
系统梳理智能体执行链路中的越狱攻击与防御并比较推理时防御
Published Sep 11
Evaluated models Qwen3.5-4B , Llama-3.1-8B-Instruct Abstract SoK 将越狱重放到智能体流水线,并用两种模型检验回复层防御的边际与代价。Mia 等人把越狱安全从单轮回复扩展到智能体的规划、记忆、工具和智能体间通信,并问既有结论在更强原生对齐下是否还成立。
提出任意字母置换密码越狱,无需微调即可诱导有害输出
Published Sep 9
Evaluated models Claude Sonnet 4 , Claude Sonnet 4.5 , Gemini 3 Flash (preview) and others7 Abstract 前沿大模型无需微调即可通过提示词学会字母置换密码,进而绕过分类器与对齐,作者呼吁关注能力提升带来的安全风险。
揭示推理加深引发的对齐坍塌,用 Reasoning Trap 放大越狱
Published Sep 8
Evaluated models Qwen3-8B , Qwen3-14B , Llama2-7B and others8 Abstract 更深推理提升题目准确率,同时提高扰动下的相对损失。作者研究扩展推理是否以对齐稳健性为代价,提出 ALR、RT 与 RRA。 。
提出 DIVA,将有害意图拆成视觉锚点与运动文本以越狱视频生成模型
Published Sep 7
Evaluated models Wan , CogVideoX , LTX-Video and others9 Abstract DIVA 用视觉锚点抑制语义漂移做视频越狱,并给出多条件安全基准 TI2VSafetyBench。DIVA 是针对带参考图的视频生成模型的免训练 black-box 越狱:用一致性机制本身堵住语义漂移这条安全逃逸路径。 。
提出 AdvPIE,在黑盒下搜索表面无害却生成有害图像的提示
Published Sep 5
Evaluated models Stable Diffusion 3.5 Large , FLUX.1-schnell , Safe-StableDiffusion 1.5 and others5 提出 EraseSAE,在文生视频模型中局部擦除指定概念
Published Sep 3
Evaluated models CogVideoX-5B , HunyuanVideo , Flux.1 [dev] Abstract EraseSAE 用单义特征局部擦除。EraseSAE 把 SAE 用于 DiT 文生视频模型的概念擦除。作者要解决的是:全局改权重或表面负提示对不齐细粒度、分布式的概念,而且会改到无关时空区域。