I am a first-year (2024 - ) Ph.D. student at University of California, San Diego supervised by Prof. Julian McAuley and closely collaborate with Prof. Zhijian Liu.
Previously, I completed my master degree at Zhejiang University in 2024 and bachelor degree at South China University of Technology in 2021.
I like building multi-modal models, focusing on multi-modal understanding, generation, and alignment, all with an emphasis on efficiency, data, and visual tokenizer.
News 🎉
- Dec. 2024 - Two papers are accepted by AAAI 2025.
- Sep. 2024 - Start Ph.D. journey at University of California, San Diego.
- Aug. 2023 - Fair Network Pruning gets accepted by ICCV 2023.
- Mar. 2023 - Efficient Dataset Distillation gets accepted by CVPR 2023 as Highlight.
Publications
Full Publications: Google Scholar
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LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation
Fangxun Shu*, Yue Liao*, Le Zhuo*, Chenning Xu*, Lei Zhang*, Guanghao Zhang*, Haonan Shi*,
Long Chen, Tao Zhong, Wanggui He, Siming Fu, Haoyuan Li, Si Liu, Hongsheng Li
arXiv
Tech report, 2024
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Audio-Visual LLM for Video Understanding
Fangxun Shu*, Lei Zhang*, Hao Jiang, Cihang Xie
arXiv
Tech report, 2023
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Filter & Align: Leveraging Human Knowledge to Curate Image-Text Data
Lei Zhang, Fangxun Shu, Tianyang Liu, Sucheng Ren, Hao Jiang, Cihang Xie
arXiv
Tech report, 2024
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Towards Fairness-aware Adversarial Network Pruning
Lei Zhang, Zhibo Wang, Xiaowei Dong, Yunhe Feng, Xiaoyi Pang, Zhifei Zhang, Kui Ren
arXiv / camera-ready
ICCV, 2023
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Accelerating Dataset Distillation via Model Augmentation
Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Li
Yao, Dongkuan Xu
arXiv / camera-ready
CVPR, 2023, Highlight
Interests
Multi-modal undestanding, generation, and alignment on efficient training and inference, data recepie: quality vs. quantity, visual tokenizer, etc.
Experiences
Services
Reviewer for CVPR, ECCV, ICCV, ICLR, ICML, and AISTATS.