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Discrete-token adaptation of frozen MLLMs enables effective robot navigation with significantly less training data than conventional approaches.
By cleverly anchoring diffusion sampling near plausible solutions and adding a lightweight residual correction, AnchorVLA achieves robust mobile manipulation with significantly reduced inference costs.
