TAP uses two-stage pretraining on unlabeled data to learn physical competence before language grounding, matching 1M-expert models with far less labeled data and showing robustness on real robots.
MIDAS: multi-layered attack detection architecture with decision optimisation
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Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs
TAP uses two-stage pretraining on unlabeled data to learn physical competence before language grounding, matching 1M-expert models with far less labeled data and showing robustness on real robots.