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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.
组合偏好奖励与评分标准奖励后训练文生图模型以抑制奖励作弊
Published Oct 2
Evaluated models FLUX.2-dev , Ideogram-4 Abstract 组合奖励后训练 FLUX.2-dev 与 Ideogram-4,并报告高于基座的胜率与 Elo。作者给出一套开放域文生图后训练配方:把人类偏好奖励和 prompt 条件的 rubric 奖励合在一起,而不是换一个新优化器。问题是单一奖励盖不住用户意图。偏好模型能看整体观感,但对“是否实现每个要求”这类稀疏属性不敏感。
提出 LineupRL,用描述到序列识别作可验证奖励训练时序描述模型
Published Oct 1 Abstract LineupRL 用统计近邻上的序列识别做可验证奖励,3B 描述器超过 SFT、两种 RL 奖励和 72B 教师。LineupRL 是给开放式时间序列描述用的 RLVR:不模仿合成参考,而奖励一条描述能否让冻结文本 LLM 从相近序列里认出目标。
提出 VoxParity,固定转写只改音频,评测语音智能体是否按行业规则改工具调用
Published Sep 28
Evaluated models MiMo-V2.6-Pro , gemini-3.7-flash , Qwen3.8-Omni and others15 Abstract VoxParity 用固定转写的音频对比和 words-only null,测量语音智能体是否按所听内容改变工具调用。VoxParity 测量语音智能体在词语不变、只有声音改变时,是否按行业规则改它所执行的工具调用。
提出 VA-Judger,用人类偏好训练联合音视频奖励模型
Published Aug 19
Evaluated models VA-Judger , LTX-2 + VA-Judger Abstract VA-Judger 用易到难的人类偏好学习做联合音视频奖励,并用于 LTX-2 后训练。VA-Judger 是面向联合音视频生成的思维链全模态奖励模型,用来替代由分维度专家指标拼成的强化学习奖励。
提出 HazardArena 基准,用孪生场景评测 VLA 的语义安全
Published Apr 14
Evaluated models OpenVLA-OFT , π0 , NORA and others4 Abstract safe-only 微调提升良性执行,也提升匹配不安全孪生上的危险完成。HazardArena 评测 VLA 在运动要求不变时,能否因语义风险而停手。
提出进程外双通道对比分类,拦截计算机使用智能体的错误点击
Published Mar 16
Evaluated models multi-modal-embed-small Abstract 感知错误可被屏幕像素对调利用。作者把 CUA 的感知失败写成安全漏洞visual confused deputy :智能体按看错的屏幕授权 click(x,y),真实落点与它以为的元素不一致。
提出 LABSHIELD,评测科学实验室智能体的安全推理与规划
Published Mar 12
Evaluated models GPT-5.2 , GPT-o3 , GPT-o4-mini and others20 You have reached the end