Qing-Hua Tan

MORE: Learning Motion-Oriented Registers for Driving World Models and Planning

By predicting future states, latent world models provide rich self-supervision for end-to-end driving, but often inherit dense features from pretrained visual encoders as their world-state interface. This creates a mismatch: visual pretraining produces information-rich, spatially dense features, but their adaptation fo...