3 papers
cs.CL2026
How to Train Your Latent Diffusion Language Model Jointly With the Latent Space
Viacheslav Meshchaninov, Alexander Shabalin, Egor Chimbulatov +4
Latent diffusion models offer an attractive alternative to discrete diffusion for non-autoregressive text generation by operating on continuous text representations and denoising e…
cs.CL2026
Cosmos: Compressed and Smooth Latent Space for Text Diffusion Modeling
Viacheslav Meshchaninov, Egor Chimbulatov, Alexander Shabalin +2
Autoregressive language models dominate modern text generation, yet their sequential nature introduces fundamental limitations: decoding is slow, and maintaining global coherence r…
cs.CL2025
TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model Encodings
Alexander Shabalin, Viacheslav Meshchaninov, Egor Chimbulatov +6
This paper presents the Text Encoding Diffusion Model (TEncDM), a novel approach to diffusion modeling that operates in the space of pre-trained language model encodings. In contra…