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Superficial reasoning in video temporal grounding can be transformed into high-quality, time-aware insights with the right optimization framework.
MLLMs are better at understanding videos than directly grounding text queries within them, and a self-correction training loop can close the gap.
Open-source UniTalking rivals closed-source giants like Veo3 and Sora2 in talking-head video realism, thanks to its multi-modal transformer and pre-trained video priors.
