"VLA-Δ: Learning Physical State Transition for VLA Models" Vision language action models learn to imitate robot actions without explicitly learning how those actions change the physical environment, which leads to failures when tasks don't go as expected. VLA-Δ addresses this by training models to predict physical state transitions, using structured changes in object positions and contacts, optical flow, and text descriptions of future state changes. These predictions are only used during…