Portrait of Xiao Huang

Xiao HUANG

Assistant Professor, Department of Computing
The Hong Kong Polytechnic University
Research interests: large language models, retrieval-augmented generation, text-to-SQL, graph representation learning, knowledge graphs, recommender systems. I am actively recruiting Ph.D. students and postdocs. Feel free to drop me emails with your CV.


Selected Publications (more papers)

Retrieval-augmented generation

  1. A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models, Qinggang Zhang, Shengyuan Chen, Yuanchen Bei, Zheng Yuan, Huachi Zhou, Zijin Hong, Junnan Dong, Hao Chen, Yi Chang, Xiao Huang, arXiv preprint arXiv:2501.13958, 2025. (GitHub)

  2. Retrieval Augmented Zero-Shot Enzyme Generation for Specified Substrate, Jiahe Du, Kaixiong Zhou, Xinyu Hong, Zhaozhuo Xu, Jinbo Xu, Xiao Huang, ICML 2025.

  3. KnowGPT: Knowledge Graph based PrompTing for Large Language Models, Qinggang Zhang, Junnan Dong, Hao Chen, Daochen Zha, Zailiang Yu, Xiao Huang, NeurIPS 2024.

LLM-based text-to-SQL

  1. Structure-Guided Large Language Model for Text-to-SQL Generation, Qinggang Zhang, Hao Chen, Junnan Dong, Shengyuan Chen, Feiran Huang, Xiao Huang, ICML, 2025.

  2. Knapsack Optimization-based Schema Linking for LLM-based Text-to-SQL Generation, Zheng Yuan, Hao Chen, Zijin Hong, Qinggang Zhang, Feiran Huang, Xiao Huang, arXiv preprint arXiv:2502.12911, 2025.

  3. Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQL, Zijin Hong, Zheng Yuan, Qinggang Zhang, Hao Chen, Junnan Dong, Feiran Huang, Xiao Huang, arXiv preprint arXiv.2406.08426, 2024.

  4. Knowledge-to-SQL: Enhancing SQL Generation with Data Expert LLM, Zijin Hong, Zheng Yuan, Hao Chen, Qinggang Zhang, Feiran Huang, Xiao Huang, ACL (Findings), 2024.

Graph representation learning

  1. Each Graph is a New Language: Graph Learning with LLMs, Huachi Zhou, Jiahe Du, Chuang Zhou, Chang Yang, Yilin Xiao, Yuxuan Xie, Xiao Huang, ACL (Findings), 2025.

Knowledge graphs

  1. Knowledge Graph Embedding Based Question Answering, Xiao Huang, Jingyuan Zhang, Dingcheng Li, Ping Li, WSDM 2019 (ACM version, Slides, Code).

Graph-based recommender systems

  1. Macro Graph Neural Networks for Online Billion-Scale Recommender Systems, Hao Chen, Yuanchen Bei, Qijie Shen, Yue Xu, Sheng Zhou, Wenbing Huang, Feiran Huang, Senzhang Wang, Xiao Huang, TheWebConf, 2024 (ACM version).

NeurIPS ICML KDD IJCAI theWebConf ACL
6 4 7 6 3 5
SIGIR AAAI WSDM CIKM PAKDD EMNLP
4 3 5 7 2 1
Total Top conference Journal TKDE
103 53 (30 first-/second-/last-author) 23 5

Services

  • Organization committee member: ICDE 2025 (PhD Symposium Chair)

  • PC member: NeurIPS 2021-2025, ICML 2021-2025, IJCAI 2020-2025, ICLR 2022-2024, AAAI 2021-2023, KDD 2019-2023, TheWebConf 2022-2023, CIKM 2019-2022, WSDM 2021-2023, SDM 2022, ICKG 2020-2021

  • Reviewer: TPAMI, IEEE TKDE, ACM TKDD, ACM Computing Surveys, ACM TOIS, IEEE Transactions on Cybernetics, IEEE Transactions on Big Data, IEEE TCSS, ACM TIST

  • Session Chair: WSDM 2023, IJCAI 2023

  • Editorial board member: Computers & Education: X Reality

Awards and Patents

Media Coverage

Biography

Dr. Xiao Huang is an Assistant Professor in the Department of Computing at The Hong Kong Polytechnic University. He earned his Ph.D. in Computer Engineering from Texas A&M University in 2020, an M.S. in Electrical Engineering from the Illinois Institute of Technology in 2015, and a B.S. in Engineering from Shanghai Jiao Tong University in 2012. His research interests encompass LLMs, retrieval-augmented generation, text-to-SQL, graph representation learning, knowledge graphs, and recommender systems. His scholarly contributions are highly regarded within the academic community, amassing over 4,800 citations. He received the Best Paper Award Honorable Mention at SIGIR 2023. He has successfully led or completed seven research projects as Principal Investigator, securing total funding exceeding 5 million HKD. He serves as a PhD Symposium Chair for ICDE 2025. Before his appointment at PolyU, he gained valuable experience as a research intern at Microsoft Research and Baidu USA.