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Task-conditioned wrist modeling boosts robot manipulation accuracy, revealing how wrist interactions can be anticipated for better performance.
Redirecting failure into actionable corrections boosts robotic manipulation success rates by nearly 32% while using an order of magnitude fewer training samples.
