9 citations · 10 across the 10 of their papers we have counts for
5 papers · 1 filter
LLaDA-o: An Effective and Length-Adaptive Omni Diffusion Model
Zebin You, Xiaolu Zhang, Jun Zhou +2
We present \textbf{LLaDA-o}, an effective and length-adaptive omni diffusion model for multimodal understanding and generation. LLaDA-o is built on a Mixture of Diffusion (MoD) fra…
Effective and Efficient Masked Image Generation Models
Zebin You, Jingyang Ou, Xiaolu Zhang +3
Although masked image generation models and masked diffusion models are designed with different motivations and objectives, we observe that they can be unified within a single fram…
Are Images Indistinguishable to Humans Also Indistinguishable to Classifiers?
Zebin You, Xinyu Zhang, Hanzhong Guo +2
The ultimate goal of generative models is to perfectly capture the data distribution. For image generation, common metrics of visual quality (e.g., FID) and the perceived truthfuln…
PoseCrafter: One-Shot Personalized Video Synthesis Following Flexible Pose Control
Yong Zhong, Min Zhao, Zebin You +3
In this paper, we introduce PoseCrafter, a one-shot method for personalized video generation following the control of flexible poses. Built upon Stable Diffusion and ControlNet, we…
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels
Zebin You, Yong Zhong, Fan Bao +3
In an effort to further advance semi-supervised generative and classification tasks, we propose a simple yet effective training strategy called dual pseudo training (DPT), built up…