publications

2026

1. ICLR

   

   OBS-Diff: Accurate Pruning For Diffusion Models in One-Shot

   Junhan Zhu, Hesong Wang, Mingluo Su, Zefang Wang, and Huan Wang

   In International Conference on Learning Representations (ICLR), 2026

   Abs arXiv HTML Code

   We propose the first training-free, one-shot pruning framework for diffusion models, demonstrating broad applicability across diverse architectures and pruning granularities.

2. CVPR

   

   Cross-Resolution Diffusion Models via Network Pruning

   Jiaxuan Ren^*, Junhan Zhu^*, and Huan Wang

   In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings, 2026

   Abs arXiv HTML

   We introduce CR-Diff, a framework that repurposes network pruning to enhance generalizability by removing adverse weights that cause degradation at non-default resolutions.

3. Preprint

   

   LVOmniBench: Pioneering Long Audio-Video Understanding Evaluation for Omnimodal LLMs

   Keda Tao, Yuhua Zheng, Jia Xu, Wenjie Du, Kele Shao, Hesong Wang, Xueyi Chen, Xin Jin, Junhan Zhu, Bohan Yu, Weiqiang Wang, Jian Liu, Can Qin, Yulun Zhang, Ming-Hsuan Yang, and Huan Wang

   2026

   Abs arXiv HTML Code

   We launch LVOmniBench, a pioneering, comprehensive benchmark for evaluating OmniLLMs in Long Audio-Video Understanding.