Mufei Li (李牧非)'s Homepage

I’m a second-year PhD student in machine learning at Georgia Institute of Technology, advised by Prof. Pan Li. My current research interests include retrieval-augmented generation (RAG) and graph generative models.

Prior to that, I was a software development engineer (SDE) at Amazon Web Services (AWS) Shanghai AI Lab. I received my bachelor’s degree in Honors Math from NYU Shanghai.

News

Jun 12, 2025	Check our new paper on better leveraging the LLM KV cache for modeling multi-doc interdependencies, Graph-KV: Breaking Sequence via Injecting Structural Biases into Large Language Models, led by Haoyu!
May 27, 2025	I’m starting a new position as Research Scientist Intern at Meta Ranking and Foundational AI! I’m based in Sunnyvale, California.
May 19, 2025	I’m honored to be a notable reviewer for ICLR 2025!
May 2, 2025	Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning has been accepted by ICML 2025! Congratulations to Rongzhe, Eli, and all the co-authors!
Apr 3, 2025	LayerDAG has been selected for spotlight presentation at ICLR 2025 workshop “Will Synthetic Data Finally Solve the Data Access Problem?”!

Selected Publications

ICML

Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning

Rongzhe Wei, Mufei Li, Mohsen Ghassemi, Eleonora Kreačić, Yifan Li, Xiang Yue, Bo Li, Vamsi K. Potluru, Pan Li, and Eli Chien

2025

arXiv Bib

@article{wei2024underestimated,
  title = {Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning},
  author = {Wei, Rongzhe and Li, Mufei and Ghassemi, Mohsen and Kreačić, Eleonora and Li, Yifan and Yue, Xiang and Li, Bo and Potluru, Vamsi K. and Li, Pan and Chien, Eli},
  booktitle = {International Conference on Machine Learning},
  year = {2025},
}

ICLR
Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation

Mufei Li, Siqi Miao, and Pan Li

In International Conference on Learning Representations, 2025

Mufei Li and Siqi Miao contributed equally to this work. This work was selected for oral presentation at [ICLR 2025 workshop on Foundation Models in the Wild](https://fm-wild-community.github.io/)

arXiv Bib Code ...⭐
@inproceedings{li2025subgraphrag, title = {Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation}, author = {Li, Mufei and Miao, Siqi and Li, Pan}, booktitle = {International Conference on Learning Representations}, year = {2025}, github_stars = {Graph-COM/SubgraphRAG}, }

ICLR Spotlight

LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation

Mufei Li, Viraj Shitole, Eli Chien, Changhai Man, Zhaodong Wang, Srinivas Sridharan, Ying Zhang, Tushar Krishna, and Pan Li

In International Conference on Learning Representations, 2025

Selected for spotlight presentation at the ICLR 2025 workshop ["Will Synthetic Data Finally Solve the Data Access Problem?"](https://synthetic-data-iclr.github.io/)

arXiv Bib Code ...⭐

@inproceedings{li2024layerdag,
  title = {Layer{DAG}: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation},
  author = {Li, Mufei and Shitole, Viraj and Chien, Eli and Man, Changhai and Wang, Zhaodong and Sridharan, Srinivas and Zhang, Ying and Krishna, Tushar and Li, Pan},
  booktitle = {International Conference on Learning Representations},
  year = {2025},
  note = {Selected for spotlight presentation at the ICLR 2025 workshop ["Will Synthetic Data Finally Solve the Data Access Problem?"](https://synthetic-data-iclr.github.io/)},
  github_stars = {Graph-COM/LayerDAG},
}

TMLR

GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?

Mufei Li, Eleonora Kreačić, Vamsi K. Potluru, and Pan Li

Transactions on Machine Learning Research, 2024

arXiv Bib Code ...⭐

@article{li2024graphmaker,
  title = {GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?},
  author = {Li, Mufei and Kreačić, Eleonora and Potluru, Vamsi K. and Li, Pan},
  year = {2024},
  journal = {Transactions on Machine Learning Research},
  github_stars = {Graph-COM/GraphMaker},
}

ACS Omega

DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science

Mufei Li, Jinjing Zhou, Jiajing Hu, Wenxuan Fan, Yangkang Zhang, Yaxin Gu, and George Karypis

ACS Omega, 2021

Bib HTML Code ...⭐

@article{dgllife,
  title = {DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science},
  author = {Li, Mufei and Zhou, Jinjing and Hu, Jiajing and Fan, Wenxuan and Zhang, Yangkang and Gu, Yaxin and Karypis, George},
  year = {2021},
  journal = {ACS Omega},
  volume = {6},
  number = {41},
  pages = {27233-27238},
  doi = {10.1021/acsomega.1c04017},
  github_stars = {awslabs/dgl-lifesci},
  dimensions = {false},
}

arXiv

Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

Minjie Wang, Da Zheng, Zihao Ye, Quan Gan, Mufei Li, Xiang Song, Jinjing Zhou, Chao Ma, Lingfan Yu, Yu Gai, Tianjun Xiao, Tong He, George Karypis, Jinyang Li, and Zheng Zhang

arXiv preprint arXiv:1909.01315, 2019

arXiv Bib Code ...⭐

@article{wang2019dgl,
  title = {Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks},
  author = {Wang, Minjie and Zheng, Da and Ye, Zihao and Gan, Quan and Li, Mufei and Song, Xiang and Zhou, Jinjing and Ma, Chao and Yu, Lingfan and Gai, Yu and Xiao, Tianjun and He, Tong and Karypis, George and Li, Jinyang and Zhang, Zheng},
  year = {2019},
  journal = {arXiv preprint arXiv:1909.01315},
  github_stars = {dmlc/dgl},
}