Hello there! I'm Gongfan Fang, currently a second-year Ph.D. student at the Learning and Vision (LV) Lab @ National University of Singapore, advised by Professor Xinchao Wang. Prior to joining LV Lab, I obtained my Bachelor's degree in 2019 and completed my Master's degree in 2022 at the Visual Intelligence and Pattern Analysis (VIPA) Lab @ Zhejiang University, where I worked under the supervision of Professor Mingli Song.

My research interests revolve around practical algorithms for efficient network training and inference. I'm also developing and maintaining several open-source projects on GitHub, including Torch-Pruning , Pytorch-MSSSIM , and DeepLabV3Plus-Pytorch .

News

Feb, 2024	DeepCache was accepted by CVPR’24. A training-free method for diffusion model acceleration.
Dec, 2023	New project SlimSAM, 0.1% Data Makes Segment Anything Slim.
Sep, 2023	Two papers LLM-Pruner & Diff-Pruning accepted by NeurIPS’23
Feb, 2023	One paper “DepGraph: Towards Any Structural Pruning” accepted by CVPR’23

Selected Publications

CVPR’23

DepGraph: Towards Any Structural Pruning

Gongfan Fang, Xinyin Ma, Mingli Song, Michael Bi Mi, and Xinchao Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

arXiv Bib PDF Code

@inproceedings{fang2023depgraph,
  title = {DepGraph: Towards Any Structural Pruning},
  author = {Fang, Gongfan and Ma, Xinyin and Song, Mingli and Mi, Michael Bi and Wang, Xinchao},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages = {16091--16101},
  year = {2023}
}

CVPR’24

DeepCache: Accelerating Diffusion Models for Free

Xinyin Ma, Gongfan Fang, and Xinchao Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

arXiv Bib Code

@inproceedings{ma2023deepcache,
  title = {DeepCache: Accelerating Diffusion Models for Free},
  author = {Ma, Xinyin and Fang, Gongfan and Wang, Xinchao},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year = {2024}
}

NeurIPS’23

LLM-Pruner: On the Structural Pruning of Large Language Models

Xinyin Ma, Gongfan Fang, and Xinchao Wang

Advances in neural information processing systems, 2023

arXiv Bib Code

@inproceedings{ma2023llmpruner,
  title = {LLM-Pruner: On the Structural Pruning of Large Language Models},
  author = {Ma, Xinyin and Fang, Gongfan and Wang, Xinchao},
  booktitle = {Advances in neural information processing systems},
  year = {2023}
}

NeurIPS’23

Structural Pruning for Diffusion Models

Gongfan Fang, Xinyin Ma, and Xinchao Wang

Advances in Neural Information Processing Systems, 2023

arXiv Bib Code

@inproceedings{fang2023structural,
  title = {Structural Pruning for Diffusion Models},
  author = {Fang, Gongfan and Ma, Xinyin and Wang, Xinchao},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2023}
}

AAAI’22

Up to 100x Faster Data-free Knowledge Distillation

Gongfan Fang, Kanya Mo, Xinchao Wang, Jie Song, Shitao Bei, Haofei Zhang, and Mingli Song

Proceedings of the AAAI Conference on Artificial Intelligence, 2022

arXiv Bib PDF Code

@inproceedings{fang2022up,
  title = {Up to 100x Faster Data-free Knowledge Distillation},
  author = {Fang, Gongfan and Mo, Kanya and Wang, Xinchao and Song, Jie and Bei, Shitao and Zhang, Haofei and Song, Mingli},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {36},
  number = {6},
  pages = {6597--6604},
  year = {2022}
}

NeurIPS’21

Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data

Gongfan Fang, Yifan Bao, Jie Song, Xinchao Wang, Donglin Xie, Chengchao Shen, and Mingli Song

Advances in Neural Information Processing Systems, 2021

arXiv Bib PDF Code

@article{fang2021mosaicking,
  title = {Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data},
  author = {Fang, Gongfan and Bao, Yifan and Song, Jie and Wang, Xinchao and Xie, Donglin and Shen, Chengchao and Song, Mingli},
  journal = {Advances in Neural Information Processing Systems},
  volume = {34},
  pages = {11920--11932},
  year = {2021}
}

IJCAI’21

Contrastive Model Inversion for Data-free Knowledge Distillation

Gongfan Fang, Jie Song, Xinchao Wang, Chengchao Shen, Xingen Wang, and Mingli Song

Proceedings of International Joint Conference on Artificial Intelligence, 2021

arXiv Bib PDF Code

@article{fang2021contrastive,
  title = {Contrastive Model Inversion for Data-free Knowledge Distillation},
  author = {Fang, Gongfan and Song, Jie and Wang, Xinchao and Shen, Chengchao and Wang, Xingen and Song, Mingli},
  journal = {Proceedings of International Joint Conference on Artificial Intelligence},
  year = {2021}
}

Preprint’19

Data-free Adversarial Distillation

Gongfan Fang, Jie Song, Chengchao Shen, Xinchao Wang, Da Chen, and Mingli Song

arXiv preprint arXiv:1912.11006, 2019

arXiv Bib Code

@article{fang2019data,
  title = {Data-free Adversarial Distillation},
  author = {Fang, Gongfan and Song, Jie and Shen, Chengchao and Wang, Xinchao and Chen, Da and Song, Mingli},
  journal = {arXiv preprint arXiv:1912.11006},
  year = {2019}
}

Education

2022.07 - Present - Ph.D. in Electrical and Computer Engineering, National University of Singapore.

2019.09 - 2022.04 - M.Eng. in Computer Science, College of Computer Science and Technology, Zhejiang University.

2015.09 - 2019.06 - B.S. in Computer Science, College of Computer Science and Technology, Zhejiang University.