Think Like a World Model, Act Like a VLA: Distilling World-Model Representations into Compact Robot Policies
This work adds one feature-alignment term to ordinary VLA training: a frozen world model is run over the training frames once and cached, and the student learns to agree with that cache, indicating a broad representational prior rather than a fragile alignment between two particular networks.