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Task-Agnostic Pretraining enables VLA models to achieve expert-level performance with orders of magnitude less labeled data, revolutionizing the scalability of embodied AI.
FlashMorph reveals that optimizing layer selection in hybrid attention models can drastically improve efficiency while maintaining performance, outperforming existing heuristic methods.
