AI RESEARCH
UniversalVTG: A Universal and Lightweight Foundation Model for Video Temporal Grounding
arXiv CS.CV
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ArXi:2604.08522v1 Announce Type: new Video temporal grounding (VTG) is typically tackled with dataset-specific models that transfer poorly across domains and query styles. Recent efforts to overcome this limitation have adapted large multimodal language models (MLLMs) to VTG, but their high compute cost and limited video context still hinder long-video grounding. We instead scale unified supervision while keeping the model lightweight. We present UniversalVTG, a single VTG model trained with large-scale cross-dataset pre.