Summary: We propose REPresentation Alignment (REPA), a method that aligns noisy input states in diffusion models with representations from pretrained visual encoders.

Dec 12, 2025 · Representation alignment (REPA) guides generative training by distilling representations from a strong, pretrained vision encoder to intermediate diffusion features. We investigate a …

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Our proposed method, REPA-E, enables stable and effective joint training of both the VAE and the diffusion model. REPA-E significantly accelerates training — achieving over 17× speedup compared …

Jan 22, 2025 · We study this by introducing a straightforward regularization called REPresentation Alignment (REPA), which aligns the projections of noisy input hidden states in denoising networks …