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Sobolev training of diffusion policies slashes trajectory optimization time by up to 20x by preventing compounding errors, even when learning from limited data.
Object-level masking in world models unlocks a 20% boost in counterfactual reasoning and drastically reduces planning costs, hinting at a path toward more efficient and robust AI agents.