One Token Per Frame: Reconsidering Visual Bandwidth in World Models for VLA Policy
OneWM-VLA compresses per-frame visual information into a single semantic token using Adaptive Attention Pooling. This reduction in visual bandwidth does not harm long-horizon control when paired with a joint flow-matching objective. The method successfully parameterizes world modules on top of pretrained models while maintaining high performance on complex tasks.