MaDeL: Manifold-Decomposed Feature Losses for Generative Modeling.

arXiv:2610.04419v1 Announce Type: cross Abstract: Generative models are often trained with isotropic objectives such as mean-squared error. For data concentrated near a low-dimensional manifold, however, such losses conflate displacement along the manifold, wh