Translation in progress Some entries still include text in the original language.
Oct 12 · Monday
Another 265 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.
构建多语言音视频 DeepFake 基准 BabelFake 并评测检测器
Published Oct 5
Evaluated models SpeechForensics , AVH-Align , (B)RAVEn Abstract BabelFake 为五语同意采集基准。BabelFake 是经同意与 IRB 批准采集的多语音视频 DeepFake 检测基准,用来把视觉操纵和语音合成拆开比较。
提出 EXE-Bench 比较 Windows 恶意软件检测器的可用性权衡
Published Jul 27
Evaluated models EmberGBDT , BBDnn , BBDnnFDRS and others15 Abstract 统一四指标后,手工特征的 EmberGBDT 综合居首,只看准确率会误导部署。EXE-Bench 用同一设置给 AI Windows 恶意软件检测器做四指标排序,而不是只比一次测试集准确率。 。
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