Youwei Liang
I’m a PhD candidate in machine learning at UC San Diego, advised by Professor Pengtao Xie. My research style is grounded in first-principles thinking, with deep understanding across computer vision, language modeling, reinforcement learning, and agentic systems. I’ve developed attention-based techniques that significantly improve the efficiency of Vision Transformers and built principled, explainable methods for improving generative image models, earning a CVPR Best Paper Award as first author.
I plan to graduate in June 2026 and am looking for Research Scientist roles in generative models, vision reasoning, multimodal learning, and closely related areas.
News
- [06/2024] Rich Human Feedback for Text-to-Image Generation received the Best Paper Award in CVPR 2024.
- [04/2023] One paper was accepted to ICML 2023.
- [01/2022] One paper was accepted as a Spotlight at ICLR 2022.
- [12/2021] I co-organized an NeurIPS 2021 Workshop: Self-Supervised Learning - Theory and Practice.
Selected Publications
(* denotes co-first authors)
Rich Human Feedback for Text-to-Image Generation
Youwei Liang*, Junfeng He*, Gang Li*, Peizhao Li, Arseniy Klimovskiy, Nicholas Carolan, Jiao Sun, Jordi Pont-Tuset, Sarah Young, Feng Yang, Junjie Ke, Krishnamurthy Dj Dvijotham, Katherine M. Collins, Yiwen Luo, Yang Li, Kai J Kohlhoff, Deepak Ramachandran, and Vidhya Navalpakkam
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR Best Paper Award), 2024.
[Code/Model] [CVPR] [arXiv] [Dataset] [Poster] [Video]
Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations
Youwei Liang, Chongjian Ge, Zhan Tong, Yibing Song, Jue Wang, and Pengtao Xie
International Conference on Learning Representations (ICLR Spotlight), 2022.
[PDF] [Code]
Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view Clustering
Youwei Liang, Dong Huang, and Chang-Dong Wang
IEEE International Conference on Data Mining (ICDM), 2019.
[PDF] [Code] [Slides] [Video]