arXiv cs.CV
· Papers
QQWorld: Quantile-Quantile Matching for World Model Regularization
arXiv:2607.28415v1 Announce Type: cross Abstract: Latent world models enable efficient planning by predicting future states in a compact representation space, but their performance depends critically on the quality of the learned latent distribution. LeWorldModel (LeWM) regularizes its latents toward an isotropic Gauss