Unified Backbone Refinement for Diffusion Models via Internal-Latent Analysis
arXiv:2607.09753v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success across diverse domains, with performance closely related to the denoising backbones that parameterize the score function. In this paper, we present a systematic, phase-aware analysis of diffusion components and show that abrupt, early-stage fluctuations in deep latents are strongly associated with artifacts. Guided by these findings, we introduce DUNE (Diffusion Unified Network refiNEr), a training-...
arXiv cs.CV
·Haksoo Lim, Myeongjin Lee, Wonjoon Chang, Jaesik Choi
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