PLaW-VLA: Predictive Latent World Modeling for Vision-Language-Action Policies
PLaW-VLA introduces a Vision-Language-Action (VLA) framework that predicts task-relevant future states using a latent world model, focusing on state transitions rather than visual details. It conditions continuous robot actions on these predicted futures via causal attention. This approach improves long-horizon control and generalization by modeling how the task evolves over time.