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ST-WAM: Semantic-Temporal World Action Model for Robust Manipulation under Visual Distribution Shifts
World Action Models (WAMs) have emerged as a promising paradigm by jointly modeling robot actions and future visual dynamics. However, their reliance on pixel-generative future supervision can entangle action-relevant state transitions with task-irrelevant visual content, limiting robustness under v