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Oct 12 · Monday
All papers Found 10 papers 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.
提出零空间激活引导 Nullify,免训练擦除指定记忆并保持效用
Published Oct 8
Evaluated models Llama-2-7B-chat-hf , Qwen3-8B 提出 SCALPEL,用对比 SAE 在表征层选择性遗忘特定事实
Published Sep 25
Evaluated models Qwen2.5-1.5B-Instruct , Llama-3.2-1B-Instruct , Gemma-2-2B-it Abstract SCALPEL 以对比稀疏特征做窄目标表征遗忘,在 TOFU 上与优化基线相当且可检查。SCALPEL 是不改基座权重的表征层遗忘方法,面向与保留数据重叠的窄目标。
提出 GUARD,在零样本 TTS 上用激活转向遗忘说话人身份以阻止再识别
Published Sep 23
Evaluated models CosyVoice2-0.5B , F5-TTS , FireRedTTS Abstract GUARD 用门控激活转向把退出说话人推向冒充相似度,以抑制再识别并保住音质。GUARD 用门控激活转向做说话人身份遗忘,使零样本 TTS 对退出说话人难以再识别。
提出 ARIA,在冻结权重上用 SAE 做推理时遗忘门控
Published Sep 15
Evaluated models DeepSeek-R1-Distill-Qwen-1.5B , Gemma-3-1B-it 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。
提出 Skill-as-API,隔离多智能体协作中的 skill 正文与系统提示词
Published Sep 1 Abstract 协议把 skill 正文留在所有者侧,四层限制发现内容、权限期限和注入拼接。Skill-as-API 是面向智能体软件工程的协调协议,用来在跨组织调用时把 skill 的代码和系统提示词留在所有者进程。作者针对三条威胁:经通道或命名空间抽取专有方法,用注入让被调用模型输出系统提示词,以及协作结束后权限继续保留。
提出 Agent MechSuits,对多轮 CLI Agent 做步级检测与子空间转向
Published Jun 22
Evaluated models LLaMA-3.1-8B , Qwen-2.5-7B , Gemma-2-9B Abstract 白盒步级探针加稀疏转向可压低三模型恶意动作,同时提高生成崩溃率。Agent MechSuits 是面向多轮 CLI 智能体的白盒、步级表示防御,并配有可执行轨迹基准 MAS。
Propose soft prompt defense AREA, re-anchoring attention to mitigate system prompt leakage
Published Jun 17
Evaluated models Llama-2-7B-chat-hf , Llama-3.1-8B-Instruct , Mistral-7B-Instruct-v0.3 and others8 Abstract The authors measure commercial prompt leakage, propose attention drift, and use AREA to strike a trade-off between usability and leakage resistance.The authors study system prompt leakage in real LLM applications and propose AREA, a mitigation method that does not modify weights.
提出 CASG,解决文生图多类别安全引导的方向冲突
Published Feb 24
Evaluated models Stable Diffusion v1.5 , SDv3 提出推理时框架 STaR,抑制大推理模型推理轨迹中的敏感内容
Published Jan 14
Evaluated models DeepSeekR1-Distill-Llama-8B Abstract STaR 以推理时轨迹调控做 LRM unlearning,作者称在 R-TOFU 上遗忘与隐私指标更好。STaR 在推理阶段约束大推理模型的整段 CoT,使指定 forget set 中的敏感内容不出现在中间步骤或最终答案里,且不更新参数。问题来自 LRM 会把敏感知识写进多步推理,而答案级遗忘在 ZeroThink、LessThink 等解码下仍可能泄漏。STaR 先判断查询是否相关并检索遗忘片段,再加安全前缀。
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