AI Research
VideoGAIA: A Benchmark for General AI Assistants on Agentic Video Understanding
Moving beyond saturated benchmarks to test the limits of agentic multimodal reasoning.
Video understanding is a fundamental task for evaluating the capabilities of multimodal large language models (MLLMs). However, existing leading models have already achieved approximately 90% accuracy on the Video-MME leaderboard, suggesting that conventional single-turn video un...
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ArXiv CS.CV
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ArXiv CS.CV
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VideoGAIA shifts the evaluation paradigm from static question-answering to dynamic, tool-integrated agentic workflows. This transition exposes significant limitations in frontier MLLMs, providing a much-needed benchmark for truly autonomous video reasoning.
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