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English(EN) MotionBlind: Probing the Illusion of Motion Understanding in Video-LLMs

新的MotionBlind基准揭示视频大语言模型在运动理解方面存在不足

作者 PulseAugur 编辑部 · [1 个来源] ·

一个名为MotionBlind的新基准已被开发出来，用于测试视频大语言模型（Video-LLMs）的运动理解能力。研究人员发现，大多数开源的Video-LLMs表现不佳，即使在呈现清晰的视觉数据时，也常常无法区分不同的运动速度或方向。虽然Gemini-3.1 Pro有所改进，但在准确评估速度方面仍有困难，这表明当前的Video-LLMs在需要真正理解运动的任务中尚不可靠。 AI

影响 突出了当前Video-LLMs的关键局限性，表明它们尚未适用于需要细微运动感知的应用。

排序理由 介绍用于评估Video-LLMs新基准的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的MotionBlind基准揭示视频大语言模型在运动理解方面存在不足

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介绍用于评估Video-LLMs新基准的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Dhairya Bhatia, Bishoy Galoaa, Oliver Fritsche, Shahid Kamal, Muhammad Obaidullah Abdul Salam, Umer Saleem, Om Rastogi, Frania Felix Chettiar, Nesli Erdogmus, Sarah Ostadabbas ·

    MotionBlind：探究视频大模型运动理解的幻觉

    arXiv:2609.09528v1 Announce Type: new Abstract: Video large language models (Video-LLMs) are increasingly used as the perceptual front end of world models, a role that assumes they can read motion: how fast something moves, which way it travels, how hard it is pushed. We show the…

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