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A unified proactive generation framework enables LLMs to form reusable factual memories from streaming video without compromising real-time perception.
TimeLens2 outperforms models with up to 397B parameters by effectively grounding temporal evidence in videos, redefining expectations for multimodal LLM capabilities.
VideoChat3 achieves unprecedented generalization in video understanding while maintaining high efficiency, outperforming larger models with just 4 billion parameters.