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Recompose and Refine Latent Reasoning Flows for Vision-Language-Action Models
Latent reasoning enables vision-language-action (VLA) models to transform multimodal observations into task-relevant internal states before generating continuous robot actions. While existing methods learn to generate or refine such states for each policy query, they discard successful reasoning aft
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