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Video-MMMU: Evaluating Knowledge Acquisition from Multi-Discipline Professional Videos.

Video-MMMU is a multi-modal, multi-disciplinary benchmark designed to assess Large Multimodal Models (LMMs) ability to acquire and utilize knowledge from videos. It features a curated collection of 300 expert-level videos and 900 human-annotated questions across six disciplines, evaluating knowledge acquisition through stage-aligned question-answer pairs: Perception, Comprehension, and Adaptation.

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What a submission needs
  • 01A public checkpoint or API endpoint
  • 02A reproduction script with frozen commit + seed
  • 03Declared evaluation environment (Python, deps)
  • 04One row per metric declared by this dataset
  • 05A contact so we can follow up on discrepancies