AI看数据视频，连因果都读不出来
让 AI 看一段带图表的新闻视频，它读得出数字，却读不出「为什么」。研究者做了第一份数据视频理解基准：961 个真实视频、6775 道题，按「读数据—跨时间推理—懂叙事」三层递进考了 19 个主流多模态大模型。最强模型 Gemini-3.1-Pro 总分 70%，但因果推理和叙事结构两项最差；多塞几帧、加字幕只对前两层有帮助，叙事理解几乎没长进。它不是你明天能用上的东西，但它划出了一条线：AI 看「会动的图表」，离人还差着「看懂故事」这一整层。
📄 原文摘要(英文)
Data video is a media form that integrates data visualization with video narrative, widely adopted in news reporting and business analysis. Compared with general video understanding, data video understanding places greater emphasis on accurately reading data from animated charts, integrating evidence across charts and time, and understanding how narrative organization and visual design communicate information. Yet existing benchmarks target either general videos or static charts, and data video understanding has not been systematically evaluated. We present DataVista, the first benchmark for data video understanding, containing 961 real-world data videos and 6,775 evaluation questions organized under a three-level progressive capability framework (data perception, temporal reasoning, narrative understanding) with 10 fine-grained question types across five topic domains. Systematic evaluation of 19 mainstream MLLMs shows that the best-performing model, Gemini-3.1-Pro, achieves 70.0% overall accuracy, still far below human expert performance, with models performing worst on Causal Reasoning and Narrative Structure. Increasing frame counts and adding subtitles mainly benefit data perception and temporal reasoning, with limited gains in narrative understanding. Further analysis of model responses identifies typical failure modes in chart reading, evidence judgment, and instruction understanding. The benchmark is available at https://github.com/HKUSTDial/DataVista.