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• DiT4DiT achieves state-of-the-art results on LIBERO benchmark with a 98.6% average success rate.result 95%
• DiT4DiT improves sample efficiency by over 10x compared to previous methods.result 90%
• DiT4DiT speeds up convergence by up to 7x compared to previous methods.result 90%
• DiT4DiT uses intermediate denoising features from video generation as temporally grounded conditions for action prediction.method 85%
• DiT4DiT achieves 50.8% success rate on RoboCasa GR1 benchmark while using substantially less training data.result 90%
• DiT4DiT demonstrates strong zero-shot generalization on the Unitree G1 robot.result 85%
• The model may struggle with tasks outside the scope of its training or require adaptation to specific hardware configurations.limitation 80%
• Video generation can serve as an effective scaling proxy for robot policy learning.technical 85%

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