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Gripper-aware Vision Language Action Models
This work introduces MiGA, a multi-gripper-aware dataset spanning five distinct gripper types across multiple robots with 103,000 demonstrations, and proposes GVLA, which combines a new multi-gripper tokenizer with adapter-based policy routing that improves zero-shot generalization or few-shot adaptation to new objects...