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By intelligently pruning attention heads based on their spatial or temporal roles and adaptively routing denoising steps through the network, PARE achieves significant computational savings in video generation without sacrificing quality.
Robots can now learn flexible, geometry-free interactions with objects directly from video, sidestepping the need for laborious 3D modeling or complex retargeting.