34 citations · 34 across the 6 of their papers we have counts for
3 papers · 1 filter
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…
Scalable Generative Modeling of Weighted Graphs
Richard Williams, Eric Nalisnick, Andrew Holbrook
Weighted graphs are ubiquitous throughout biology, chemistry, and the social sciences, motivating the development of generative models for abstract weighted graph data using deep n…
Hybrid Models with Deep and Invertible Features
Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh +2
We propose a neural hybrid model consisting of a linear model defined on a set of features computed by a deep, invertible transformation (i.e. a normalizing flow). An attractive pr…