Where Success Breaks: Failure-Boundary Learning for Robust Vision-Language-Action Models
The DLS method introduces Failure-Boundary Learning to improve Vision-Language-Action models by identifying exactly where closed-loop behavior transitions from recoverable error to task failure. It uses a Discover–Localize–Shape pipeline, employing semantic progress localization and directional boundary shaping based on digital twin rollouts. This focuses training on the critical moments of breakdown rather than just fitting expert demonstrations.