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  "text": "Meet DiT4DiT, the FIRST video generation architecture for humanoid robot control. 🤖✨ \n\nBy treating video generation as a world model, we give robots real \"physical intuition.\" 🔥 \nThe Results:\n🚀 >10x better sample efficiency & up to 7x faster convergence! \n🏆 SOTA on LIBERO (98.6%) & RoboCasa-GR1 (50.8%). \n🦾 Zero-shot generalization on the Unitree G1 humanoid using just monocular vision (1x speed, fully autonomous). \n🧠 How it works: We couple a Video DiT with an Action DiT via a dual flow-matching objective. Instead of relying on fully reconstructed future frames, we extract \"intermediate denoising features\" to guide action prediction—simple but highly effective! \n\nCheck out the paper, real-world videos, and project page here: https://t.co/Ml0AA8PKqA \n\n#EmbodiedAI #Robotics #MachineLearning #WorldModels",
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