Saining Xie· @sainingxie · X·· 2026-06-03AI 评分67
AI 导读
研究团队推出VSTAT基准测试，用于评估多模态大语言模型（MLLMs）在视频中追踪动态状态的能力。测试任务看似简单，包括计数杯子、识别键入的文字、统计翻页次数等，人类可以轻松完成，但当前MLLMs表现欠佳。该测试旨在推动视觉状态跟踪这一前沿方向的发展，解决模型从不完整、有噪声的视觉观察中建立和更新内部世界状态的核心挑战。
正文 · 原文
how does the brain build and track an internal state of the world from (possibly incomplete and noisy) visual observations?
i believe visual state tracking will be the grand challenge for vision in the coming years, and i hope this benchmark can be a useful starting line. enjoy!
Can MLLMs actually track what's happening in a video? Introducing VSTAT 🎯, our new benchmark for visual state tracking. The tasks are simple: count cups, read typed words, count page flips. Humans solve them easily. MLLMs don't. https://vision-x-nyu.github.io/vstat-site/ 🧵 [1/11]在 X 查看被引用的帖子
来源：Saining Xie · x.com