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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 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 HTN 协调层，在执行前固定多服务器 MCP 工具顺序
Published Sep 28 Abstract 作者提供可重放的 MCP 协调架构，但未用实测基线量化相对 LLM 的成本改善。HTN 规划在这里承担跨服务器工具协调层的角色。 作者关注 MCP 宿主逐步选择工具时的复现、推理成本和执行前检查问题。
提出成本感知的 MCP 编排框架，用确定性利用图与免费层模型做自动化渗透测试
Published Sep 16 Abstract 确定性利用图加免费层级联在十次自建运行上测得付费成本为零。PentestChain 是一个十阶段、经 MCP 暴露的自动渗透框架，用确定性利用图把 7B 本地模型挡在利用关键路径之外，并把每次交战的美元成本当作实测指标。 。
提出结构化 JSON 后门，经投毒 LoRA 在机器人控制中触发恶意动作
Published Apr 5
Evaluated models Llama-3.1-8B-Instruct , Gemma-2-9B-IT , DeepSeek-R1-Distill-Llama-8B and others4 You have reached the end