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English(EN) Through a PRISM, Clearly: Step-Sequence Reasoning for Mistake Recognition in Procedural Videos

新的PRISM系统利用语言接地技术识别视频中的程序性错误

研究人员开发了PRISM,一个新颖的系统,通过将视频片段与语言进行接地并将它们映射到程序状态来识别程序化视频中的错误。PRISM利用一个在正确执行上训练的隐马尔可夫模型来识别步骤内容和顺序中的错误。该系统展示了其训练过的本地解码器带来的持续收益,并表明语义角色标注提高了在各种基准测试中的错误检测能力,确立了语言接地作为程序性错误推理的有效接口。 AI

影响 确立了语言接地作为视频中显式程序性错误推理的有效接口。

排序理由 该项目是一篇研究论文,详细介绍了一种新的视频分析方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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新的PRISM系统利用语言接地技术识别视频中的程序性错误

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该项目是一篇研究论文,详细介绍了一种新的视频分析方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Olga Loginova, Oleksandr Bezrukov, Frank Keller ·

    Through a PRISM, Clearly: Step-Sequence Reasoning for Mistake Recognition in Procedural Videos

    arXiv:2610.31117v1 Announce Type: cross Abstract: Procedural mistake recognition requires identifying deviations from valid multi-step activities. We study post-completion recognition from videos with benchmark-provided step boundaries. We introduce PRISM (Procedural mistake Reco…