CoRE-VLA: Towards Scalable and Robust Vision-Language-Action Modeling via Conditional Routing of Experts
CoRE-VLA addresses brittle Vision-Language-Action (VLA) models by making action generation context-conditioned sparse computation. It introduces Conditional Routing of Experts, which allows robots to selectively use auxiliary sensors when available and fall back reliably when they are missing or absent. This enables graceful degradation and improves performance across diverse tasks.