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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.
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Proposes the semantic watermark SemField, which still identifies the attribution of generated text after paraphrasing and structural changes.
Published Oct 8
Evaluated models Llama-3.2-1B , Qwen3-1.7B , OPT-1.3B Abstract Training-independent document-level semantic watermark.SemField is a zero-bit semantic watermark embedded by the provider at generation time and detected later with a key, used to identify the provider's own model text after paraphrasing and sentence-level structural changes.
提出 UNTAG，绕过开源权重模型的 trigger-tag 滥用检测
Published Oct 2
Evaluated models Llama2 (7B) , Llama3 (8B) , Qwen2.5 (7B) Abstract 作者用 UNTAG 评估 trigger-tag，认为其不能充当开放权重滥用检测的主要边界。UNTAG 是针对开放权重 LLM 上条件滥用检测 trigger-tag 的统一攻击评估：信号可以在解码期注入，也可以写进权重，但攻击者若能改输出或改已发布权重，检测可以失效。
提出 ORBIT 框架，评测多智能体防御对合谋等威胁的效果
Published Sep 27
Evaluated models GPT-5.4 , Claude Sonnet 4.6 , Qwen3-235B and others5 Abstract ORBIT 用六层配置比较多智能体防御，逐动作监控不迁移到合谋。
测试编程智能体被诱导或自主篡改自身执行轨迹的行为
Published Sep 25
Evaluated models GPT-5.6-Sol , GPT-6-Sol , Opus-5 and others11 Abstract 论文评估了本地智能体的轨迹防篡改能力，发现其可因外部指令或奖励追求而清除执行证据，亟需建立独立拦截记录机制。这是一项针对本地大模型智能体执行轨迹完整性与安全防篡改边界的实证研究。
提出 plan injection 攻击，植入良性伪装计划以绕过思维链监视器
Published Sep 15
Evaluated models Qwen2.5-Coder-7B-Instruct , Qwen3-8B , DeepSeek-R1-0528 and others6 Abstract 论文指出模型会将外部上下文中的伪装计划改写为自身推理，使思维链监视器失效甚至反向合理化恶意行为。
提出 MOLE 基准，评测监控器对 AI 智能体内部威胁的检出能力
Published Sep 7
Evaluated models GPT-5.3 Chat , GPT-5.5 , GPT-4.1 and others15 Abstract MOLE 构建了智能体内部威胁检测基准，作者指出高漏检现状与推理痕迹的防御价值，并展示了监控策略优化空间。MOLE 是首个针对前沿 AI 实验室智能体内部威胁检测的开放基准，旨在评估在有限每日审查预算与日常研发业务背景下识别恶意账号的能力。 。
提出分片监督，将评判标准分配给独立调用以抵御展示攻击
Published Aug 6
Evaluated models Claude Opus 4.8 , Claude Sonnet 4.6 , Claude Opus 4.6 and others4 Abstract 论文揭示决策负载是大模型监督的独立瓶颈，提出分片与辩论机制有效分离注意力与平衡证据，在多项高难度基准上实现稳健评判。本文系统研究了大语言模型在执行多标准监督与评判时的决策负载瓶颈及其安全风险。
提出 GhostPrint，用低秩微调让弱模型骗过指纹审计
Published Jun 15
Evaluated models Gemma-1.1-2B , Qwen2-1.5B , Phi-3-mini Abstract GhostPrint 以 PEFT 让弱模型骗过部分指纹。GhostPrint 讨论恶意推理提供方能否只用低秩更新，让更弱的模型在用户的 black-box 指纹审计里看起来像宣传中的强模型。
提出 Meerkat，聚类并搜索 Agent 轨迹库以定位跨轨迹安全违规
Published Apr 14
Evaluated models GPT-5.4 , GPT-5.4-mini , Qwen3.5-397B-A17B and others5 Abstract Meerkat 用聚类与智能体搜索定位跨轨迹违规，并在真实评测轨迹中找出脚手架泄题与奖励黑客。Meerkat 是事后审计方法，用来在智能体轨迹仓库里找出单条看不出、合在一起才违反自然语言安全属性的见证。
提出 Adaptive Stealing，自适应窃取印章以擦除或伪造水印
Published Apr 13
Evaluated models OPT-2.7b , Llama3-8b Abstract AS 用逐步选印章做水印伪造与擦除，作者称其攻击效果高于固定策略的 WS。AS 是一种窃取生成式 LLM 水印的算法，用来在密钥和检测接口不可用时伪造或擦除水印。
提出 CORVUS，用 LoRA 伪装内部遥测以绕过幻觉检测器
Published Jan 19
Evaluated models Llama-2-7B-Chat , Vicuna-7B (v1.5) , Llama-3-8B-Instruct and others4 Abstract 作者称内部遥测在自适应模型侧对抗下易被操纵，CORVUS 通过轻量适配器微调降低了多种幻觉检测器的效果。
Attacks arXiv 2509.09112 · Sep 11, 2025 提出字符级扰动与遗传算法去除 LLM 水印
Published Sep 11, 2025
Evaluated models OPT-1.3B , LLaMA-3-8B Abstract 字符级扰动靠更大攻击范围移除水印。这篇工作评估推理时 LLM 水印在黑盒、有限查询下的移除难度，并比较字符级、token 级和句子级编辑。
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