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VideoVista is presented, a versatile multilingual and multidomain video comprehension benchmark, built via scalable, quality-controlled automatic QA generation and manual refinement, and released at https://github.com/HITsz-TMG/VideoVista.
This work introduces VideoChat3, a fully open, efficient, and generalist video-centric MLLM, which surpasses prior open-source models with equal or larger parameter counts with only 4B parameters and higher efficiency.
Across seven benchmarks, TimeLens2-2B outperforms all size-matched baselines on every benchmark, while the 4B and 8B variants achieve state-of-the-art performance, surpassing open-source models with up to 397B parameters.
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