Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs

A new research paper introduces a Task-Agnostic Pretraining framework for Vision-Language-Action models, which achieves superior performance with minimal expert demonstrations. The framework first learns transferable motor priors from cheap, unlabeled interaction data and then grounds these priors in language using minimal expert data.

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