Paper recorded by Signals 4 on 2026-10-13 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-13 on arXiv · recorded by Signals 4 on 2026-10-14
Category: cs.CV · 计算机视觉 · first seen 2026-10-14
Pixel-space diffusion models provide an appealing alternative to latent-space diffusion models by directly modeling raw images without relying on a learned tokenizer. However, scaling pixel-space models has predominantly followed dense strategies, tightly coupling model capacity with active computation. In this work, we show that standard LLM-style Mixture-of-Experts (MoE) architectures can be eff