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The Temporal Ratio reveals how attention shifts between future and present frames can predict a model's ability to generalize compositional tasks in video-action contexts.
Existing robotic methods falter in tackling fundamental physical reasoning challenges, as evidenced by KinDER's rigorous benchmark evaluation.
Ditch the noisy averaging: this method unlocks stable, long-horizon robot planning with diffusion models by enforcing consistency on *clean* data estimates.