 CFG in the fake
score network. This flexible setup improves diversity without sacrificing
alignment. Comprehensive experiments on SD1.5 and SDXL demonstrate
state-of-the-art performance in both one-step and few-step generation settings,
along with robustness to the absence of real images. Our efficient PyTorch
implementation, along with the resulting one- and few-step distilled
generators, will be released publicly as a separate branch at
https://github.com/mingyuanzhou/SiD-LSG.</p>
            
          