Universal Inverse Distillation for Matching Models with Real-Data Supervision (No GANs)

TL;DR

While achieving exceptional generative quality, modern diffusion, flow, and other matching models suffer from slow inference, as they require many steps of iterative generation. Recent distillation methods address this problem by training efficient one-step generators under the guidance of a pre-trained teacher model.

Opening excerpt from the authors’ abstract. source