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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.
提出 LTBD，用可学习分隔符隔离可信指令与不可信数据
Published Oct 8
Evaluated models Llama3-8B-Instruct , Llama3.1-8B-Instruct , Falcon3-7B-Instruct and others4 Abstract LTBD 只训练四个分隔符嵌入。LTBD 是一种不改基座权重的提示注入防御：只学习用来标出可信指令与不可信数据边界的四个 token 嵌入。
提出临时可见性协议，限制持续摄入 RAG 向量库的投毒暴露
Published Oct 5 Abstract 用截止期限制未核验可见时长。这篇工作给持续摄入的 RAG 向量库一个失败关闭的临时可见性协议，把协议能限制的未核验暴露和依赖检测器的中毒暴露分开。
提出利用共享冷却的跨租户干扰攻击，并设计租户隔离机制
Published Oct 4 Abstract 揭示网关共享冷却漏洞，提出来源检查与租户隔离防御。
提出 ASA 与 AttestMCP，度量并降低 LLM 对输入序列扰动的敏感
Published Oct 2
Evaluated models Gemma-3-27B-Instruct , Gemma-3-4B-Instruct , Llama-3.2-3B-Instruct and others12 提出契约约束的工具调用修复协议，在执行前拦截非法补丁
Published Sep 29
Evaluated models 2B rank-8 LoRA , 0.8B rank-4 LoRA 提出 Provenance-Aware Transformers，隔离不可信来源防御间接提示注入
Published Sep 18
Evaluated models SmolLM2-360M-Instruct , LLaMA-3-8B-Instruct , Qwen2.5-7B-Instruct and others4 提出意图驱动本地框架 Veilmind，净化发往远程模型的提示词
Published Sep 10
Evaluated models Veilmind-4B Abstract 本地模型按意图净化提示词，在 Uprise 上给出两个隐私-效用工作点。本地侧的意图驱动净化，用来降低用户提示词发往不受信任远程模型时的敏感属性暴露。
提出 Sentinel-RL，将拓扑处置从 LLM 卸载到受约束图策略
Published Sep 4
Evaluated models HetGAT , PPO Abstract Sentinel-RL 用图编码器与 PPO 承担拓扑决策，LLM 负责叙述与门控，并在 LANL 上报告检测与时延。Sentinel-RL 是面向 SOC 的神经符号架构：拓扑决策离开 LLM，改由认证图上的 HetGAT 与 PPO 完成。
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