邝炜瑞, Weirui Kuang
@ALIBABA GROUP @TONGYI LAB
About Me
Welcome to my homepage! I am a researcher at Tongyi Lab, Alibaba Group. I received a B.S. degree in Applied Mathematics and M.E. degree in Computer Applications Technology from Renmin University of China in 2018 and 2021, respectively. My research interests include graph representation learning, federated learning, and LLMs. I have published several papers in ICML, KDD, NeurIPS, VLDB, and AAAI and served as the reviewer for top-tier conferences such as ICLR, KDD, NeurIPS, ICML, and WWW. And I'm one of the main developers of the open-source project AgentScope and FederatedScope and am passionate about contributing to open-source projects related to my research interest. Additionally, our team provide algorithm support for the Tongyi App.
Experience
Alibaba Tongyi Lab
Senior Machine Learning Engineer • June 2021 — Present
- Multi-Agent System (2024): AgentScope, Tongyi APP
- Federated Learning for LLM (2023): FederatedScope-LLM
- AutoML (2022): FedHPO-Bench
- Graph Representation Learning (2021)
Alibaba DAMO Academy
Research Intern • April 2021 — June 2021
- Graph Representation Learning: KDD Cup 2021 OGB-LSC 9th Place
Alibaba Cloud
Research Intern • March 2020 — March 2021
- Block Storage Cardinality Estimation
Education
Renmin University of China
Postgraduate in School of Information • 2018 — 2021
Major in Computer Science and Technology, Graph Learning
Advisor: Zhewei Wei
Renmin University of China
B.S. in School of Information • 2014 — 2018
Major in Mathematics and Applied Mathematics
Publications
2024
-
“FederatedScope-LLM: A Comprehensive Package for
Fine-tuning Large Language Models in Federated
Learning”
KDD 2024 - Weirui Kuang*, Bingchen Qian*, Zitao Li, Daoyuan Chen, Dawei Gao, Xuchen Pan, Yuexiang Xie, Yaliang Li, Bolin Ding and Jingren Zhou. -
“When Transformer Meets Large Graphs: An Expressive
and Efficient Two-View Architecture”
TKDE 2024 - Weirui Kuang*, Zhen Wang*, Yaliang Li, Zhewei Wei and Bolin Ding. -
“Is Sharing Neighbor Generator in Federated Graph
Learning Safe?”
TKDE 2024 - Liuyi Yao, Zhen Wang, Yuexiang Xie, Yaliang Li, Weirui Kuang, Daoyuan Chen, Bolin Ding
2023
-
“FedHPO-Bench: A Benchmark Suite
for Federated Hyperparameter Optimization”
ICML 2023 - Zhen Wang*, Weirui Kuang*, Ce Zhang, Bolin Ding, Yaliang Li. -
“FederatedScope: A Comprehensive and Flexible Federated
Learning Platform via Message Passing”
VLDB 2023 - Xie, Yuexiang*, Zhen Wang*, Dawei Gao, Daoyuan Chen†, Liuyi Yao†, Weirui Kuang†, Yaliang Li, Bolin Ding and Jingren Zhou.
2022
-
“pFL-Bench: A Comprehensive Benchmark for
Personalized Federated Learning”
NeurIPS 2022 - Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding. -
“FederatedScope-GNN: Towards a Unified, Comprehensive
and Efficient Package for Federated Graph Learning”
KDD 2022, ADS Best Paper - Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou. -
“Graph Neural Networks with Nodewise Architecture”
KDD 2022 - Zhen Wang, Yaliang Li, Zhewei Wei, Weirui Kuang, Bolin Ding.