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VideoChat3 is a fully open, efficient, and generalist video-centric multimodal large language model that introduces Inflated 3D Vision Transformer (I3D-ViT) and Adaptive Frame Resolution for streaming video perception, along with scalable video data synthesis pipelines, achieving superior performance with only 4B parameters.
RefereeBench introduces the first large-scale benchmark with 925 curated sports videos and 6,475 QA pairs to evaluate whether video MLLMs can reliably act as multi-sport referees. Evaluation of state-of-the-art models shows current MLLMs fall short (≤60% accuracy), struggling with rule application and temporal grounding despite their generic video understanding capabilities.