5 papers
RSIgen: Reciprocal Self-Improvement for Agentic Visual Generation
Yidi Liu, Haozhe Wang, Jie Xiao +3
Agentic visual generation produces experience that can improve the native understanding (agent) and generation roles of a unified multimodal backbone, but task success alone does n…
When Does Visual Generation Help Visual Understanding in Unified Multimodal Models?
Yubo Zhu, Zhehan Kan, Jingyi Yang +6
Unified multimodal models (UMMs) can perform both understanding and generation, raising a central question: can visual generation improve understanding? Existing evaluations provid…
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…
BACON: Improving Clarity of Image Captions via Bag-of-Concept Graphs
Zhantao Yang, Ruili Feng, Keyu Yan +13
Advancements in large Vision-Language Models have brought precise, accurate image captioning, vital for advancing multi-modal image understanding and processing. Yet these captions…