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.
“
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.
构建多语言音视频 DeepFake 基准 BabelFake 并评测检测器
Published Oct 5
Evaluated models SpeechForensics , AVH-Align , (B)RAVEn Abstract BabelFake 为五语同意采集基准。BabelFake 是经同意与 IRB 批准采集的多语音视频 DeepFake 检测基准，用来把视觉操纵和语音合成拆开比较。
提出校准重合成方法，以生成器反演保真度认证真实图像并防御对抗扰动
Published Oct 5 Abstract 论文提出基于反演保真度与阈值校准的健全认证框架，在对抗扰动下维持错误率界限，并指出真实内容可认证性随生成器演进而萎缩。
提出 Mind2Web-Injection 评测网页 Agent 视觉注入护栏
Published Sep 2
Evaluated models GPT-5.6-luna , Qwen3-VL-32B , Qwen3-VL-8B and others6 Abstract 作者称检测、定位和反事实响应在六个 VLM 上可分开。Mind2Web-Injection 用来检查网页截图护栏的判决是否对齐到该用的画面证据。 。
提出机器遗忘式生成图像检测，用遗忘前后特征相似度区分自然图与生成图
Published Aug 1
Evaluated models DINOv2 ViT-S/14 , DINOv2 ViT-B/14 , DINOv2 ViT-L/14 and others9 Abstract 作者用剪枝或 LoRA 遗忘拉开生成图与自然图的特征相似度，并在多个检测基准上报告结果。这篇工作把 AI 生成图像检测写成对预训练视觉模型的机器遗忘：原模型对两类图像损失都低，剪枝后生成图特征变得更不像原模型。
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 Jul 16
Evaluated models CLIPViT (ViT-B/16) , CLIPCNN (ResNet-50) , ALBEF and others4 Abstract GeoDetect 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。
Proposes out-of-process dual-channel comparison classification to intercept erroneous clicks by computer-use agents
Published Mar 16
Evaluated models multi-modal-embed-small Abstract Perception errors can be exploited by swapping screen pixels.The authors frame CUA's perception failure as a security vulnerability, visual confused deputy : the agent authorizes click(x,y) based on a misread screen, and the actual landing point differs from the element it believes it is clicking.
提出 RA-Det，利用鲁棒性不对称检测 AI 生成图像
Published Mar 2 Abstract RA-Det 把扰动下特征漂移差变成检测信号，平均 ACC 高于表中通用检测器，但不是每行最高。RA-Det 是合成图像检测器，用扰动下的表示稳定性差异代替外观痕迹。
提出 WAInjectBench 评测网页 Agent 的提示注入检测
Published Oct 2, 2025
Evaluated models GPT-4o , Mistral-7B-Instruct-v0.1 , Llama-Prompt-Guard-2-86M and others8 Abstract WAInjectBench 比较网页智能体的提示注入检测：显式线索可被部分检出，隐蔽攻击大多漏检。WAInjectBench 是网页智能体提示注入检测的基准。作者要看现有检测器能否发现这类攻击：攻击者改网页，使智能体执行目标动作，而不是用户任务。作者称这是首个此类综合基准。
You have reached the end