2 papers
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
TUBE: Tangent Upper Bound on Evidence for Discrete Diffusion Language Models
Arseny Ivanov, Sergei Kholkin, Vladislav Gromadskii +3
Log-likelihood is a standard metric for evaluating generative models. Unfortunately, in contrast to autoregressive models (ARMs), discrete diffusion models generally do not admit e…