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Allocating additional computation during decision-making boosts long-horizon robot manipulation success by significantly enhancing subtask prediction accuracy.
WorldDiT achieves robust action generation and visual modeling without the need for bulky pretrained models, setting a new standard for efficiency in robotic policies.
