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Even state-of-the-art dexterous manipulation policies fail to generalize, achieving only 38.5% success on novel tasks after training on related ones.
Language-action pretraining can lead to VLA policies that are not only more robust but also less dependent on visual cues, achieving up to 45% higher success rates in real-world tasks.