3 papers
cs.CV2026
Registers Matter for Pixel-Space Diffusion Transformers
Nikita Starodubcev, Ilia Sudakov, Ilya Drobyshevskiy +2
Vision Transformers (ViTs) are known to exhibit high-norm patch-token outliers that degrade feature map quality, a problem effectively mitigated by register tokens. As diffusion mo…
cs.CV2026
Revisiting Autoregressive Models for Generative Image Classification
Ilia Sudakov, Artem Babenko, Dmitry Baranchuk
Class-conditional generative models have emerged as accurate and robust classifiers, with diffusion models demonstrating clear advantages over other visual generative paradigms, in…
cs.CV2026
Scale-wise Distillation of Diffusion Models
Nikita Starodubcev, Ilya Drobyshevskiy, Denis Kuznedelev +2
Recent diffusion distillation methods have achieved remarkable progress, enabling high-quality -step sampling for large-scale text-conditional image and video diffusion mo…