Xi-Hui Liu

Learning to predict the visual consequences of actions significantly boosts policy performance and generalization, while simultaneously improving world model accuracy.

By compressing future observations into a learned "condition space," WoG enables VLA models to generate more precise actions and generalize better than models relying on direct future prediction.