One-Step is Enough: Sparse Autoencoders for Text-to-Image Diffusion Models

arXiv — cs.CV•Wednesday, October 29, 2025 at 4:00:00 AM

A recent study highlights the potential of sparse autoencoders (SAEs) in enhancing text-to-image diffusion models, particularly focusing on SDXL Turbo. This research is significant as it aims to improve the interpretability of features in these models, which has been a challenge in the field. By applying SAEs, the study suggests that we can achieve better control and analysis of the generated images, paving the way for advancements in AI-generated content.

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