Positive-Direction Matching

Positive-Direction Matching addresses branch asymmetry in classifier-free guidance for diffusion distillation

A new arXiv paper identifies a failure mode called Negative Branch Asymmetry (NBA) in on-policy diffusion distillation (OPD) when combined with classifier-free guidance (CFG), showing that naive guided velocity matching can produce antagonistic branch-error dynamics. The authors introduce Positive-Direction Matching (PDM), a branch-aware training objective that separately constrains the positive prediction and the CFG conditional direction. The method is validated on dense-to-sparse video control, where it improves robustness to inference guidance scales compared to naive guided matching.