Kuan Li Homepage

About Me

I am currently a second-year PhD student at CSE HKUST under the supervision of Prof. Minhao Cheng and Prof. Shuai Wang. I obtained my M.E. degree from Institute of Computing Technology, Chinese Academy of Sciences (ICT, CAS) supervised by Prof. Xiang Ao, and completed my B.E. degree in Electrical Engineering and Automation at Beihang University.

If you have any questions regarding my work or are interested in collaborating with me, please contact me via email.

Contact information

Email: likuan.ppd@gmail.com

Wechat: Kuan_ppd

Research interests

My research interests lie in agent learning and machine learning on graphs. Currently, my work focuses on LLM agents, particularly on developing efficient methods to enable LLMs to leverage external tools for solving tasks that they cannot complete autonomously.

Publications

LaRA: Benchmarking Retrieval-Augmented Generation and Long-Context LLMs – No Silver Bullet for LC or RAG Routing

Kuan Li, Liwen Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Shuai Wang, Minhao Cheng.
In ICML 2025. [Download paper] [code]

Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective

Kuan Li, YiWen Chen, Yang Liu, Jin Wang, Qing He, Minhao Cheng, Xiang Ao.
In ICLR 2024. [Download paper] [code]

FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs

Yang Liu, Xiang Ao, Fuli Feng, Yunshan Ma, Kuan Li, Tat-Seng Chua, Qing He.
In KDD 2023. [Download paper]

Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective

Kuan Li, Yang Liu, Qing He, Xiang Ao.
In ICLR 2023. [Download paper] [code]

Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN

Kuan Li, Yang Liu, Xiang Ao, Jianfeng Chi, Jinghua Feng, Hao Yang, Qing He.
In KDD 2022. [Download paper] [code]

AUC-oriented Graph Neural Network for Fraud Detection

Mengda Huang, Yang Liu, Xiang Ao, Kuan Li, Jianfeng Chi, Jinghua Feng, Yang Hao and Qing He.
In WWW 2022. [Download paper]