1 citations · 1 across the 8 of their papers we have counts for
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SimFlow: Simplified and End-to-End Training of Latent Normalizing Flows
Qinyu Zhao, Guangting Zheng, Tao Yang +4
Normalizing Flows (NFs) learn invertible mappings between the data and a Gaussian distribution. Prior works usually suffer from two limitations. First, they add random noise to tra…
Confidence and Dispersity as Signals: Unsupervised Model Evaluation and Ranking
Weijian Deng, Weijie Tu, Ibrahim Radwan +3
Assessing model generalization under distribution shift is essential for real-world deployment, particularly when labeled test data is unavailable. This paper presents a unified an…
DiSA: Diffusion Step Annealing in Autoregressive Image Generation
Qinyu Zhao, Jaskirat Singh, Ming Xu +3
An increasing number of autoregressive models, such as MAR, FlowAR, xAR, and Harmon adopt diffusion sampling to improve the quality of image generation. However, this strategy lead…
ARINAR: Bi-Level Autoregressive Feature-by-Feature Generative Models
Qinyu Zhao, Stephen Gould, Liang Zheng
Existing autoregressive (AR) image generative models use a token-by-token generation schema. That is, they predict a per-token probability distribution and sample the next token fr…