Carving World Action Modeling
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WALL-WM: Carving World Action Modeling at the Event Joints
arXiv:2606.01955v1 Announce Type: new Abstract: WALL-WM is a World Action Model that shifts video-action learning from chunk-centric optimization to event-grounded Vision-Language-Action pretraining, using semantically coherent action events as the atomic unit of learning. Existing WAMs commonly initialize from multimodal or video foundation models and then optimize fixed-length action chunks conditioned directly on the current observation and instruction. Although convenient, this...
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