most citedTransAgent: Transfer Vision-Language Foundation Models with Heterogeneous Agent Collaboration

1 citations · 1 across the 3 of their papers we have counts for

collaborators

9 papers

cs.CV2025

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin

Fangyikang Wang, Hubery Yin, Lei Qian +9

The diffusion models (DMs) have demonstrated the remarkable capability of generating images via learning the noised score function of data distribution. Current DM sampling techniq…

cs.LG2025

Efficiently Access Diffusion Fisher: Within the Outer Product Span Space

Fangyikang Wang, Hubery Yin, Shaobin Zhuang +7

Recent Diffusion models (DMs) advancements have explored incorporating the second-order diffusion Fisher information (DF), defined as the negative Hessian of log density, into vari…

cs.CV2025

Video-GPT via Next Clip Diffusion

Shaobin Zhuang, Zhipeng Huang, Ying Zhang +6

GPT has shown its remarkable success in natural language processing. However, the language sequence is not sufficient to describe spatial-temporal details in the visual world. Alte…

cs.CV2025

V-Stylist: Video Stylization via Collaboration and Reflection of MLLM Agents

Zhengrong Yue, Shaobin Zhuang, Kunchang Li +2

Despite the recent advancement in video stylization, most existing methods struggle to render any video with complex transitions, based on an open style description of user query.…

cs.CV2025

TimeStep Master: Asymmetrical Mixture of Timestep LoRA Experts for Versatile and Efficient Diffusion Models in Vision

Shaobin Zhuang, Yiwei Guo, Yanbo Ding +7

Diffusion models have driven the advancement of vision generation over the past years. However, it is often difficult to apply these large models in downstream tasks, due to massiv…

cs.CV2025

WeGen: A Unified Model for Interactive Multimodal Generation as We Chat

Zhipeng Huang, Shaobin Zhuang, Canmiao Fu +7

Existing multimodal generative models fall short as qualified design copilots, as they often struggle to generate imaginative outputs once instructions are less detailed or lack th…