Jul 2026
Contrastive-Augmented Flow Matching for Style-Content Disentanglement
Comparative Augmented Flow Matching (CAtFM) is introduced, a framework that integrates contrastive regularization into an invertible flow matching formulation to promote structured content-style representations and provides a simple way to couple discriminative constraints with deterministic transport, improving disentanglement and robustness under distribution shift.
Yusong Li, Pingchuan Ma, Ming Gui et al.
· arXiv.org · 0 citations