AI RESEARCH

Information-Theoretic Constraints for Continual Vision-Language-Action Alignment

arXiv CS.AI

ArXi:2603.13335v1 Announce Type: cross When deployed in open-ended robotic environments, Vision--Language--Action (VLA) models need to continually acquire new skills, yet suffer from severe catastrophic forgetting. We observe that this degradation is related to the deterioration of cross-modal information structure, where dependencies among visual observations, language instructions, and actions progressively diffuse during continual adaptation. But existing continual learning methods fail to preserve such cross-modal information dependencies.