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.

  4. Cost-efficient Knowledge-based Question Answering with Large Language Models, Junnan Dong, Qinggang Zhang, Chuang Zhou, Hao Chen, Daochen Zha, Xiao Huang, NeurIPS 2024.

  5. Modality-Aware Integration with Large Language Models for Knowledge-based Visual Question Answering, Junnan Dong, Qinggang Zhang, Huachi Zhou, Daochen Zha, Pai Zheng, Xiao Huang, ACL, 2024.

Large language model evaluation

  1. Benchmarking Large Language Models via Random Variables, Zijin Hong, Hao Wu, Su Dong, Junnan Dong, Yilin Xiao, Yujing Zhang, Zhu Wang, Feiran Huang, Linyi Li, Hongxia Yang, Xiao Huang, arXiv preprint arXiv:2501.11790, 2025.

  2. CLR-Bench: Evaluating Large Language Models in College-level Reasoning, Junnan Dong, Zijin Hong, Yuanchen Bei, Feiran Huang, Xinrun Wang, Xiao Huang, arXiv preprint arXiv:2410.17558, 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.

  2. Taming Language Models for Text-attributed Graph Learning with Decoupled Aggregation, Chuang Zhou, Zhu Wang, Shengyuan Chen, Jiahe Du, Qiyuan Zheng, Zhaozhuo Xu, Xiao Huang, ACL, 2025.

Knowledge graphs

  1. Entity Alignment with Noisy Annotations from Large Language Models, Shengyuan Chen, Qinggang Zhang, Junnan Dong, Wen Hua, Qing Li, Xiao Huang, NeurIPS, 2024.

  2. Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs, Shengyuan Chen, Yunfeng Cai, Huang Fang, Xiao Huang, Mingming Sun, NeurIPS, 2023.

  3. Hierarchy-Aware Multi-Hop Question Answering over Knowledge Graphs, Junnan Dong, Qinggang Zhang, Xiao Huang, Keyu Duan, Qiaoyu Tan, Zhimeng Jiang, TheWebConf, 2023 (ACM version).

  4. Active Ensemble Learning for Knowledge Graph Error Detection, Junnan Dong, Qinggang Zhang, Xiao Huang, Qiaoyu Tan, Daochen Zha, Zihao Zhao, WSDM, 2023 (ACM version).

  5. 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).

  2. Graph Cross-Correlated Network for Recommendation, Hao Chen, Yuanchen Bei, Wenbing Huang, Shengyuan Chen, Feiran Huang, Xiao Huang, IEEE Transactions on Knowledge and Data Engineering, 2024.

  3. Adaptive Popularity Debiasing Aggregator for Graph Collaborative Filtering, Huachi Zhou, Hao Chen, Junnan Dong, Daochen Zha, Chuang Zhou, Xiao Huang, SIGIR, 2023 (ACM version).

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 large language models, 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 4,000 citations. Notably, 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.