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University of Amsterdam
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Sparse video reasoning can outperform dense observation models by learning to extract crucial temporal evidence from limited frames, even without explicit VQA annotations.
Adapting general VLMs to e-commerce data can substantially boost performance without sacrificing broad multimodal capabilities, a finding demonstrated through a large-scale study.
