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SIDO enables static-trained policies to excel in dynamic environments, achieving higher success rates in moving object manipulation without sacrificing static performance.
Ditch the noisy averaging: this method unlocks stable, long-horizon robot planning with diffusion models by enforcing consistency on *clean* data estimates.
