Bowen Xue, Zizhang Li, Hong-Xing Yu, Jiajun Wu · Unified action world model

UniAction

UniAction is a unified action-conditioning framework for world models, described in an arXiv preprint by Bowen Xue, Zizhang Li, Hong-Xing Yu and Jiajun Wu. Existing action-conditioned world models are usually built for one action type, which fragments limited action-annotated data across separate models. UniAction represents any action as a sparse set of action elements, each with a discrete semantic identity and a continuous spatiotemporal coordinate. These coordinates are mapped into the pretrained video model's native positional space, so different actions condition one shared model in the same way. The authors add cardinality-calibrated attention to correct bias from differing action representation granularities. They evaluate on four action forms (force, camera control, hand pose and robot pose) and report that it follows actions better than the conditioning alternatives, and that one jointly trained model beats action-specific experts. The page gives no numerical results, and does not state a licence or code release.