Preprint
Aug 2026
GWM-VLA: Geometry-Aware Latent World Modeling for Vision-Language-Action Learning
GWM-VLA is proposed, a geometry-aware latent world modeling framework for VLA learning that combines geometry-aware multi-view state encoding, global context-conditioned target-view prediction, and shared latent-action representations grounded by robot-action supervision.
Yanping Zhao, Hang Yu, Yi-Wei Wang et al.
· 2 citations