MEND: Label-Free Detection, Localisation, and Correction of Latent Hallucination in World Models
MEND is a single network designed to find and fix 'latent hallucination' in world models—when predicted future states are impossible. It uses a conditional score field to detect how far predictions are from valid states, localize errors to specific image patches, and apply a correction direction during inference without needing any error labels.