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Oct 12 · Monday
Another 233 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 OmniConfess，冻结候选并按通道重打分以缓解全模态幻觉
Published Oct 2
Evaluated models Qwen2.5-Omni-7B , Qwen3-Omni-30B-A3B , Nemotron-3-Nano-Omni-30B 提出训练无关的 SECRET，对问题表征做源条件转向以缓解音视频模型幻觉
Published Sep 29
Evaluated models VideoLLaMA2-AV-7B , Qwen2.5-Omni-7B , Qwen3-Omni-30B-A3B Abstract SECRET 在问题状态上做源条件转向，三个 AVLLM 上减轻了跨模态接地幻觉。SECRET 是一种训练无关的问题状态转向方法，用来减轻 AVLLM 的 source-confused grounding hallucination。
提出 AEGIS，用中层内部信号选择性激活后层适配器拦截音频越狱
Published Sep 24
Evaluated models Qwen2-Audio-7B , VITA-1.5 , Ultravox v0.5 and others6 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。
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