Kun Wu

RecMorph is introduced, a topology-guided spatial recurrent architecture that uses recurrent sequence computation to jointly perform cross-limb communication and representation transformation and shows that topology-guided recurrent transformation provides an effective and efficient communication mechanism for Generalized Morphology Control and remains effective when transferred from procedural bodies to physical robot platforms.

Dynamically adjusting visual importance at test time can significantly enhance action prediction accuracy in VLA models.