42 citations · 52 across the 15 of their papers we have counts for
5 papers · 1 filter
Normalizing Flows are Capable Generative Models
Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran +7
Normalizing Flows (NFs) are likelihood-based models for continuous inputs. They have demonstrated promising results on both density estimation and generative modeling tasks, but ha…
TypeScore: A Text Fidelity Metric for Text-to-Image Generative Models
Georgia Gabriela Sampaio, Ruixiang Zhang, Shuangfei Zhai +4
Evaluating text-to-image generative models remains a challenge, despite the remarkable progress being made in their overall performances. While existing metrics like CLIPScore work…
dMel: Speech Tokenization made Simple
Richard He Bai, Tatiana Likhomanenko, Ruixiang Zhang +3
Large language models have revolutionized natural language processing by leveraging self-supervised pretraining on vast textual data. Inspired by this success, researchers have inv…
Improving GFlowNets for Text-to-Image Diffusion Alignment
Dinghuai Zhang, Yizhe Zhang, Jiatao Gu +4
Diffusion models have become the de-facto approach for generating visual data, which are trained to match the distribution of the training dataset. In addition, we also want to con…
How Far Are We from Intelligent Visual Deductive Reasoning?
Yizhe Zhang, He Bai, Ruixiang Zhang +4
Vision-Language Models (VLMs) have recently demonstrated incredible strides on diverse vision language tasks. We dig into vision-based deductive reasoning, a more sophisticated but…