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Thank you, I'm not used to reading this kind of research papers but I think I got the gist of it now.

Can this architecture be used to distill models that need fewer timesteps like LCMs or SDXL turbo?

Both Latent Consistency Models and Adversarial Diffusion Distillation (the method behind SDXL Turbo) are methods that do not depend on any specific properties of the backbone. So, as Hourglass Diffusion Transformers are just a new kind of backbone that can be used just like the Diffusion U-Nets in Stable Diffusion (XL), these methods should also be applicable to it.

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