3 papers
cs.LG2026
A Tale of Two Temperatures: Simple, Efficient, and Diverse Sampling from Diffusion Language Models
Theo X. Olausson, Metod Jazbec, Xi Wang +4
Much work has been done on designing fast and accurate sampling for diffusion language models (dLLMs). However, these efforts have largely focused on the tradeoff between speed and…
cs.LG2021
Lossless Compression with Probabilistic Circuits
Anji Liu, Stephan Mandt, Guy Van den Broeck
Despite extensive progress on image generation, common deep generative model architectures are not easily applied to lossless compression. For example, VAEs suffer from a compressi…
cs.LG2019
Autoregressive Text Generation Beyond Feedback Loops
Florian Schmidt, Stephan Mandt, Thomas Hofmann
Autoregressive state transitions, where predictions are conditioned on past predictions, are the predominant choice for both deterministic and stochastic sequential models. However…