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cs.LG2026
IDRF: Inverse-Distilled Reward Fine-tuning of Masked Discrete Diffusion Models
Vladislav Gromadskii, David Li, Samson Gourevitch +4
Masked discrete diffusion models offer a promising alternative to autoregressive generation, but iterative sampling can be costly, and intractable sequence likelihoods complicate r…
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…