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Clip: Under review as a conference paper at ICLR 2024 SDXL:IMPROVINGLATENTDIFFUSIONMODELS FOR HIGH-RESOLUTIONIMAGESYNTHESIS Anonymous authors Paper under double-blind review ABSTRACT We presentStable Diffusion XL(SDXL), a latent diffusion model for text-to-image synthesis. Compared to previous versions ofStable Diffusion,SDXLleverages a three times larger UNet backbone, achieved by significantly increasing the number of attention blocks and including a second text encoder. Further, we design multiple novel conditioning schemes and trainSDXLon multiple aspect ratios. To ensure highest quality results, we also introduce arefinement modelwhich is used to improve the visual fidelity of samples generated bySDXLusing a post-hoc image-to-imagetechnique. We demonstrate thatSDXLimproves dramatically over previous versions ofStable Diffusionand achieves results competitive with those

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