Unified world-action modelExpert
UniWAM: Unified World-Action Model
UniWAM is a preprint introducing a unified robot foundation model that combines a vision-language reasoner, a video-generation world model, and an action predictor. It reaches 99.2% success on LIBERO, 92.6% on LIBERO-Plus OOD perturbations, 68.32% on RoboTwin 2.0 Clean2Random, and 82.5% real-robot instruction-following rate. The work matters because it shows how co-training on robot, human egocentric, and VQA data can improve robustness, generalization, and long-horizon manipulation.