1 citations · 1 across the 4 of their papers we have counts for
4 papers
Learning to Expand Images for Efficient Visual Autoregressive Modeling
Ruiqing Yang, Kaixin Zhang, Zheng Zhang +2
Autoregressive models have recently shown great promise in visual generation by leveraging discrete token sequences akin to language modeling. However, existing approaches often su…
ActVAR: Activating Mixtures of Weights and Tokens for Efficient Visual Autoregressive Generation
Kaixin Zhang, Ruiqing Yang, Yuan Zhang +2
Visual Autoregressive (VAR) models enable efficient image generation via next-scale prediction but face escalating computational costs as sequence length grows. Existing static pru…
Diverse and Tailored Image Generation for Zero-shot Multi-label Classification
Kaixin Zhang, Zhixiang Yuan, Tao Huang
Recently, zero-shot multi-label classification has garnered considerable attention for its capacity to operate predictions on unseen labels without human annotations. Nevertheless,…
Positive Label Is All You Need for Multi-Label Classification
Zhixiang Yuan, Kaixin Zhang, Tao Huang
Multi-label classification (MLC) faces challenges from label noise in training data due to annotating diverse semantic labels for each image. Current methods mainly target identify…