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cs.LG2026
IDLM: Inverse-distilled Diffusion Language Models
David Li, Nikita Gushchin, Dmitry Abulkhanov +4
Diffusion Language Models (DLMs) have recently achieved strong results in text generation. However, their multi-step sampling leads to slow inference, limiting practical use. To ad…
cs.LG2025
Inverse Bridge Matching Distillation
Nikita Gushchin, David Li, Daniil Selikhanovych +3
Learning diffusion bridge models is easy; making them fast and practical is an art. Diffusion bridge models (DBMs) are a promising extension of diffusion models for applications in…
cs.LG2024
Diffusion & Adversarial Schrödinger Bridges via Iterative Proportional Markovian Fitting
Sergei Kholkin, Grigoriy Ksenofontov, David Li +6
The Iterative Markovian Fitting (IMF) procedure, which iteratively projects onto the space of Markov processes and the reciprocal class, successfully solves the Schrödinger Bridge…