Andrew presented his paper, “CLaD: Planning with Grounded Foresight via Cross-Modal Latent Dynamics” at CVPR 2026, held from June 3rd – 7th, 2026, in Denver, USA.
He suggested CLaD, a framework that models the joint evolution of proprioceptive and semantic states under robotic actions through asymmetric cross-attention. By enforcing consistency over cross-modal transitions and using self-supervised objectives, the model predicts grounded latent foresights without experiencing representation collapse. These predicted foresights condition a diffusion policy for action generation, achieving a high success rate on long-horizon tasks with significantly fewer parameters than large vision-language-action (VLA) models.