3 papers
cs.CL2026
Representation-Space MMD for Diffusion Language Models
Ilya Drobyshevskiy, Ilia Sudakov, Maksim Semenov +7
We introduce a post-training method for diffusion language models (DLMs) that minimizes Maximum Mean Discrepancy (MMD) between generated and reference distributions in the feature…
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…