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These results demonstrate a scalable route for consolidating independently acquired robot skills into a continually growing generalist policy and show that the student recovers a large proportion of teacher performance while achieving near-zero forgetting.
While Vision-Language-Action (VLA) models pretrained on large-scale robot datasets provide a strong foundation for robot manipulation, their performance can degrade when adapted to new tasks with limited task-specific demonstrations. Retrieval offers a practical way to reuse existing demonstrations for data-efficient a...
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