About Me
Gen Li is a third-year Ph.D. student at Clemson University, under the supervision of Prof. Xiaolong Ma and co-advised by Prof. Linlke Guo. His primary research focuses on efficient Machine Learning, algorithm-hardware co-design for mobile devices, and fairness and robustness in broad AI applications.
🔥 News
09/2024, One paper is accepted in NeurIPS 2024
09/2024, One paper is accepted in S&P 2025
07/2024, One paper is accepted in ECCV 2024
05/2024, Two papers are accepted in ICML 2024.
01/2024, One paper is accepted in ICLR 2024.
09/2023, One paper is accepted in NeurIPS 2023.
02/2023, One paper is accepted with spotlight presentation at the ICLR SNN workshop.
02/2023, One paper is accepted as highlight paper (top 2.5%) in CVPR 2023.
Selected Publications
Data Overfitting for On-Device Super-Resolution with Dynamic Algorithm and Compiler Co-Design
Gen Li, Zhihao Shu, Jie Ji, Minghai Qin, Fatemeh Afghah, Wei Niu, Xiaolong Ma
ECCV '24 · Acceptance rate: 27.9%
Advancing Dynamic Sparse Training by Exploring Optimization Opportunities
Jie Ji*, Gen Li*, Lu Yin, Minghai Qin, Geng Yuan, Linke Guo, Shiwei Liu, Xiaolong Ma
ICML '24 · Acceptance rate: 27.5%
Outlier weighed layerwise sparsity (owl): A missing secret sauce for pruning llms to high sparsity
Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Gen Li, Ajay Jaiswal, Mykola Pechenizkiy, Yi Liang, Michael Bendersky, Zhangyang Wang, Shiwei Liu
ICML '24 · Acceptance rate: 27.5%
NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization
Gen Li, Lu Yin, Jie Ji, Wei Niu, Minghai Qin, Bin Ren, Linke Guo, Shiwei Liu, Xiaolong Ma
ICLR '24
Dynamic Sparsity Is Channel-Level Sparsity Learner
Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
NeurIPS '23 · Acceptance rate: 26.1%
Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting
Gen Li, Jie Ji, Minghai Qin, Wei Niu, Bin Ren, Fatemeh Afghah, Linke Guo, Xiaolong Ma
CVPR '23 · Highlight paper: top 2.5%