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Oct 13 · Tuesday
All papers Found 14 papers Another 227 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.
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.
用翻译前缀做跨语言训练数据提取，恢复英语训练文本中的 PII
Published Oct 5
Evaluated models GPT-Neo 1.3B , GPT-Neo 2.7B , GPT-J 6B and others7 Abstract 跨语言 TDE 能恢复英语记忆的 PII，转移随多语训练和措辞保真变化。这篇工作检验训练数据抽取是否跨语言：英语段落里记住的 PII，能否被其他语言的前缀逐字抽出。
提出 VEX-Bench 评测 LLM 生成虚假信息的核查复杂度
Published Sep 28
Evaluated models Claude Sonnet 4.5 , Gemini 3.1 Pro , GPT-5.4 and others7 Abstract VEX-Bench 用筛查时的五维复杂度衡量虚假信息对核查容量的占用，并报告生成与核查的成本差。VEX-Bench 把 LLM 虚假信息的风险从“能否生成”改成“筛查时会占用多少核查容量”。
提出 PrivDrift 基准，审计话题漂移后的用户秘密复述
Published Sep 25
Evaluated models GPT-OSS-120B , DeepSeek-R1 , Qwen3-VL-235B 提出扩散潜空间地理扰动防御，抑制视觉语言模型泄露精确地理位置
Published Sep 18
Evaluated models GPT-4.1 , GPT-5 , Gemini 2.5 Pro and others5 利用加密思维块的跨模型重放，诱导弱模型逐字转写专有推理链
Published Aug 11
Evaluated models Claude Opus 4.8 , Claude Sonnet 4.6 , Claude Haiku 4.5 and others13 Abstract 论文揭示了客户端加密思维块跨模型互换漏洞，提出了低成本提取方法并给出防御方案。
Extract system instructions with encoding and structured requests, and harden them by rewriting with CoT
Published Apr 1
Evaluated models GPT-4.1-mini , GPT-3.5-turbo , Gemini-2.5-flash and others7 Abstract Encoded requests can elicit system instructions after a direct refusal.This work evaluates and hardens the confidentiality of LLM system instructions under encoded extraction. The authors are concerned with: when direct extraction has been rejected, whether the model still surrenders protected content when the same request is rewritten as a formatting or encoding task.
提出 LFT 多轮框架，评测模型对欺诈与网络犯罪的可执行协助
Published Feb 25
Evaluated models Claude Sonnet 3.5 , Claude Sonnet 3.7 , Claude Sonnet 4 and others14 Abstract 作者称低努力文本诱导下，多轮 LFT 中模型对三类犯罪的信息协助有限。作者给出一套由执法与政策专家校验的多轮评测，用来估计文本模型经由信息提供，对欺诈和网络犯罪有多少可执行协助。
Proposes a user-side defense TRACE-RPS, anonymizing text before sharing and appending suffixes to suppress attribute inference.
Published Feb 12
Evaluated models Llama2-7B-Chat , Llama2-13B-Chat , Llama3.1-8B-Instruct and others10 Abstract User-side TRACE plus RPS/MPS reduces LLM inference accuracy for sensitive attributes before sharing.This is a user-side defense: reducing LLM inference of sensitive attributes before the text is made public, rather than modifying attack prompts or weakening model reasoning.
提出 JustAsk，用在线技能选择提取模型系统提示词
Published Jan 29
Evaluated models anthropic/claude-opus-4.5 , openai/gpt-5.2-codex , GPT-5.2 and others19 提出 ChartAttack，用恶意提示驱动代码模型生成误导图表
Published Jan 19
Evaluated models Claude-4.6-Sonnet , GPT-4o , Gemini-2.5-Flash and others20 Abstract ChartAttack 生成不改数据的误导图，降低 MLLM 与人类的图表问答准确率。ChartAttack 研究恶意提示能否让 MLLM 在不改数据的情况下生成误导图表，并量化这些图对其他 MLLM 和人类图表问答的影响。
Attacks arXiv 2512.16059 · Dec 18, 2025 提出 ContextLeak，用金丝雀成员推断审计私有 ICL 泄漏
Published Dec 18, 2025
Evaluated models Llama3.3-70b , Qwen2.5-72b , GPT-4.1 and others6 Abstract ContextLeak 审计私有 ICL 的 worst-case 泄漏。ContextLeak 是一套用成员推断审计私有 ICL 的框架，目标是给 worst-case 泄漏一个经验下界，而不是只引用理论 ε。
Attacks arXiv 2509.09488 · Sep 11, 2025 提出 SeedSnitch 与 PromptPirate，恢复种子后窃取扩散提示词
Published Sep 11, 2025
Evaluated models Stable Diffusion 3.5 Large , Stable Diffusion 3.5 Medium , Stable Diffusion 3.5 Turbo and others4 You have reached the end