UniWAM: Unified World-Action Model
UniWAM integrates a physical reasoner, world generator, and action predictor into a single model using a Mixture-of-Transformers architecture. It jointly learns semantic understanding of the physical world, visual generation, and action prediction by connecting language reasoning with video and action modalities through joint attention. This creates a generalist robot capable of robust instruction following across diverse scenarios.