17 citations · 18 across the 6 of their papers we have counts for
6 papers
Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing
Xinjie Zhang, Peng Zhang, Shicheng Zheng +21
Large-scale visual generators are increasingly capable but costly to train, fine-tune, and deploy. We introduce Mage-Flow, a compact 4B-scale generative stack for efficient text-to…
GenArena: How Can We Achieve Human-Aligned Evaluation for Visual Generation Tasks?
Ruihang Li, Leigang Qu, Jingxu Zhang +6
The rapid advancement of visual generation models has outpaced traditional evaluation approaches, necessitating the adoption of Vision-Language Models as surrogate judges. In this…
MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment
Tianze Wang, Dongnan Gui, Yifan Hu +2
Reinforcement Learning from Human Feedback (RLHF) has shown promise in aligning large language models (LLMs). Yet its reliance on a singular reward model often overlooks the divers…
Improving Handwritten OCR with Training Samples Generated by Glyph Conditional Denoising Diffusion Probabilistic Model
Haisong Ding, Bozhi Luan, Dongnan Gui +2
Constructing a highly accurate handwritten OCR system requires large amounts of representative training data, which is both time-consuming and expensive to collect. To mitigate the…
Zero-shot Generation of Training Data with Denoising Diffusion Probabilistic Model for Handwritten Chinese Character Recognition
Dongnan Gui, Kai Chen, Haisong Ding +1
There are more than 80,000 character categories in Chinese while most of them are rarely used. To build a high performance handwritten Chinese character recognition (HCCR) system s…
GlyphControl: Glyph Conditional Control for Visual Text Generation
Yukang Yang, Dongnan Gui, Yuhui Yuan +4
Recently, there has been an increasing interest in developing diffusion-based text-to-image generative models capable of generating coherent and well-formed visual text. In this pa…