Vision Language Actions using reasoning as action tokens.

Vision–Language–Action (VLA) models use reasoning steps (e.g., plans, chains of thought, subgoals, or symbolic decisions) as action tokens, so the model first generates explicit intermediate reasoning that guides downstream control. These reasoning tokens bridge high-level intent and low-level actions, improving interpretability, long-horizon planning, and task generalization across environments.