algorithm avoids step-specific networks and integrates seamlessly into existing
pipelines, achieving state-of-the-art performance on SDXL at 1024x1024
resolution. To mitigate the alignment-diversity trade-off when real text-image
pairs are available, we introduce a Diffusion GAN-based adversarial loss
applied to the uniform mixture and propose two new guidance strategies:
Zero-CFG, which disables CFG in the teacher and removes text conditioning in
the fake score network, and Anti-CFG, which applies negative