29 citations · 38 across the 5 of their papers we have counts for
5 papers
A Survey on Latent Reasoning
Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng +30
Large Language Models (LLMs) have demonstrated impressive reasoning capabilities, especially when guided by explicit chain-of-thought (CoT) reasoning that verbalizes intermediate s…
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
Kaiwen Xue, Yuhao Zhou, Shen Nie +4
Bayesian flow networks (BFNs) iteratively refine the parameters, instead of the samples in diffusion models (DMs), of distributions at various noise levels through Bayesian inferen…
Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data
Jingyang Ou, Shen Nie, Kaiwen Xue +4
Discrete diffusion models with absorbing processes have shown promise in language modeling. The key quantities to be estimated are the ratios between the marginal probabilities of…
One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale
Fan Bao, Shen Nie, Kaiwen Xue +7
This paper proposes a unified diffusion framework (dubbed UniDiffuser) to fit all distributions relevant to a set of multi-modal data in one model. Our key insight is -- learning d…
All are Worth Words: A ViT Backbone for Diffusion Models
Fan Bao, Shen Nie, Kaiwen Xue +4
Vision transformers (ViT) have shown promise in various vision tasks while the U-Net based on a convolutional neural network (CNN) remains dominant in diffusion models. We design a…