WorldBridge: Bridging Video and Action Experts for Task Generalization in World Action Models

WorldBridge proposes a World Action Model (WAM) that connects separate video and action experts through structured attention and trains them with joint flow matching. On RoboTwin 2.0, using only in-distribution video-action supervision yields a 25.07% success rate on out-of-distribution tasks; adding task videos without action labels raises it to 55.90%, and adding one action-labeled demonstration per task further raises it to 70.70%.