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Bridging the gaps in physical intelligence could enable agents to learn and adapt in real-world scenarios more effectively than ever before.
Stop blasting your diffusion models with a single, static reward signal: fine-grained credit assignment across denoising steps and objectives unlocks better image and video generation.
Forget imitation: reward-aware trajectory shaping lets few-step generative models outperform their multi-step teachers.
