Machine Heart
May 21, 2026 · Artificial Intelligence
RAEv2: How a Simple Extra Operation Makes Image Generation Train Ten Times Faster
The RAEv2 framework replaces traditional VAEs by summing multiple layers of pretrained vision encoders, combines RAE with REPA for complementary semantic and spatial gains, and leverages free guidance, achieving up to ten‑fold faster convergence, higher image quality, and lower compute on ImageNet‑256 diffusion training.
Diffusion ModelsRAEv2Representation Autoencoder
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