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Robots can learn faster and perform better by strategically choosing *when* to be unpredictable, achieving both multimodal expressivity and deterministic efficiency.
Robots can now better understand implicit instructions in cluttered scenes, choosing the knife over the scissors when told to "cut the apple," thanks to a new benchmark and neural network architecture designed to handle functionally similar objects.