12 citations · 12 across the 7 of their papers we have counts for
10 papers
Focusing on What Matters: Saliency-Harnessing Accurate Routing for Diffusion MoE
Haoyou Deng, Keyu Yan, Chaojie Mao +4
Mixture-of-Experts (MoE) architectures have emerged as a powerful paradigm for scaling diffusion models in visual generation. Recent advancements have focused on adaptively allocat…
Wan-Image: Pushing the Boundaries of Generative Visual Intelligence
Chaojie Mao, Chen-Wei Xie, Chongyang Zhong +55
We present Wan-Image, a unified visual generation system explicitly engineered to paradigm-shift image generation models from casual synthesizers into professional-grade productivi…
Wan-Weaver: Interleaved Multi-modal Generation via Decoupled Training
Jinbo Xing, Zeyinzi Jiang, Yuxiang Tuo +15
Recent unified models have made unprecedented progress in both understanding and generation. However, while most of them accept multi-modal inputs, they typically produce only sing…
DenseGRPO: From Sparse to Dense Reward for Flow Matching Model Alignment
Haoyou Deng, Keyu Yan, Chaojie Mao +4
Recent GRPO-based approaches built on flow matching models have shown remarkable improvements in human preference alignment for text-to-image generation. Nevertheless, they still s…
Unison: A Fully Automatic, Task-Universal, and Low-Cost Framework for Unified Understanding and Generation
Shihao Zhao, Yitong Chen, Zeyinzi Jiang +5
Unified understanding and generation is a highly appealing research direction in multimodal learning. There exist two approaches: one trains a transformer via an auto-regressive pa…
Wan: Open and Advanced Large-Scale Video Generative Models
Team Wan, Ang Wang, Baole Ai +58
This report presents Wan, a comprehensive and open suite of video foundation models designed to push the boundaries of video generation. Built upon the mainstream diffusion transfo…