I am currently a research assistant professor at the School of Computing and Data Science of HKU, collaborating with Professor Chao Huang. I also work with Professor Ben Kao. My research works lie in data science, with a focus on applications ranging from Information Retrieval, Robust and Efficient Graph Mining, User Behavior Modeling, AI for Urban Science, and Trustworthy AI. I received my Ph.D. and Bachelor degrees in computer science at South China University of Technology (SCUT) adviced by Professor Yong Xu.

Research Interests

• Foundation Models, Large Language Models,
• Graph Learning, Self-Supervised Learning,
• Recommendation, Spatio-Temporal Modeling.

News

• [10/2024] - We release LightRAG, a simple and fast RAG system
• [10/2024] - Our ACM MM paper DiffMM is recognized as Best Paper Nomination & Hornorable Mention Award of MM'2024
• [10/2024] - Three papers are accepted by WSDM'2025
• [10/2024] - Our work OpenGraph on Graph Foundation Model is accepted by EMNLP'2024
• [09/2024] - Listed in World's Top 2% Scientists by Stanford University
• [08/2024] - We release AnyGraph, a graph foundation model in the wild
• [08/2024] - Our work UrbanGPT is accepted by KDD'2024, and is featured in Most Influential Papers of KDD'2024 (Rank 10th / 559)
• [06/2023] - Recognized as AI 2000 Most Influential Scholars (2022-2023) by Aminer in Data Mining (Rank 15th) and Information Retrieval (Rank 19th)
• [05/2024] - Ou work RLMRec on LLM-enhanced recommendation, is accepted by WWW'2024, and recognized as Most Influential Papers of WWW'2024 (Rank 1st / 405)
• [06/2023] - We release SSLRec, a useful programming library for self-supervised recommendation
• [05/2023] - Our paper AutoCF on automated self-supervised recommendation, is selected as Spotlight Paper & Best Paper Nomination of WWW'2023 (16 / 323), and is recognized as Most Influential Papers of WWW'2023 (Rank 10th / 365)
• [04/2023] - Our ICLR paper LightGCL is selected as Spotlight Paper of ICLR'2023 (Top 25%)
• [07/2022] - Our SIGIR'2022 papers HCCF and KGCL on contrastive recommendation models, are featured in Most Influential Papers of SIGIR'2022 (Rank 3rd and 2nd / 161)
• [02/2022] - My co-authored paper CML is selected as Best Paper Candidate of WSDM'2022
• [12/2021] - I received the He-Jingtang Innovation Prize (with only two winners throughout the university) and and graduate from SCUT in advance
• [09/2021] - National Scholarship and Presidential Scholarship for Ph.D. Candidates
• [07/2021] - Our work MB-GMN on multi-behavior recommendation is accepted by SIGIR'2021, and recognized as Most Influential Papers of SIGIR'2021 (Rank 13th / 151)

Selected Publications

I have published 15 first-authored papers in top-tier publication venues in different fields such as Information Retrieval (SIGIR, WWW, TOIS), Data Mining (KDD, WSDM, TKDE), Artificial Intelligence (ICLR, ICML, AAAI, IJCAI, TNNLS), and Database (ICDE). My publications gained some highly selective awards, including Eleven Most Influential Papers, Two Spotlight Papers, Two Most Cited Papers, and Three Best Paper Nominations. For a full list of my publications, please refer to my Google Scholar page.

• [WSDM'25] "Heterogeneous Graph Collaborative Filtering"
  ACM International Conference on Recommender Systems
  L. Xia, M. Xie, Y. Xu and C. Huang
  [pdf] [code]

• [EMNLP'24] "OpenGraph: Towards Open Graph Foundation Models"
  Conference on Empirical Methods in Natural Language Processing
  L. Xia, B. Kao, and C. Huang
  [pdf] [code]

• [KDD'24] "UrbanGPT: Spatio-Temporal Large Language Models"
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  Z. Li, L. Xia, J. Tang, Y. Xu, L. Xia, D. Yin, and C. Huang
  Most Influential Papers of KDD'24 (Rank 10 / 559)
  [pdf] [code]

• [MM'24] "DiffMM: Multi-Modal Diffusion Model for Recommendation"
  ACM International Conference on Multimedia
  Y. Jiang, L. Xia, W. Wei, D. Luo, K. Lin, and C. Huang
  Best Paper Nomination & Hornorable Mention Award
  [pdf] [code]

• [WWW'24] "RLMRec: Representation Learning with Large Language Models for Recommendation"
  ACM The Web Conference
  X. Ren, W. Wei, L. Xia, L. Su, S. Cheng, J. Wang, D. Yin and C. Huang
  Most Influential Papers of WWW'24
  [pdf] [code]

• [WWW'23] "Automated Self-Supervised Learning for Recommendation"
  ACM The Web Conference
  Spotlight Paper & Best Paper Nomination (16 / 323), Most Influential Papers of WWW'23 (Rank 10 / 323)
  L. Xia, C. Huang, C.Z. Huang, K. Lin, T. Yu and B. Kao
  [pdf] [code]

• [WWW'23] "Graph-less Collaborative Filtering"
  ACM The Web Conference
  L. Xia, C. Huang, J. Shi and Y. Xu
  [pdf] [code]

• [ICDE'23] "Disentangled Graph Social Recommendation"
  IEEE International Conference on Data Engineering
  L. Xia, Y. Shao, C. Huang, Y. Xu, H. Xu and J. Pei
  [pdf] [code]

• [WWW'23] "Debiased Contrastive Learning for Sequential Recommendation"
  ACM The Web Conference
  Y. Yang, C. Huang, L. Xia, C.Z. Huang, D. Luo and K. Lin
  Most-Influential Papers of WWW'23 (Rank 5 / 323)
  [pdf] [code]

• [WWW'23] "Multi-Modal Self-Supervised Learning for Recommendation"
  ACM The Web Conference
  W. Wei, C. Huang, L. Xia and C. Zhang
  Most Influential Papers of WWW'23 (Rank 4 / 323)
  [pdf] [code]

• [ICLR'23] "LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation"
  International Conference on Learning Representations
  Selected as Spotlight Paper (Top 25%)
  X. Cai, C. Huang, L. Xia and X. Ren
  [pdf] [code]

• [KDD'23] "Knowledge Graph Self-Supervised Rationalization for Recommendation"
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  Y. Yang, C. Huang, L. Xia, and C. Huang
  Most Influential Papers of KDD'23 (Rank 11 / 497)
  [pdf] [code]

• [KDD'23] "Adaptive Graph Contrastive Learning for Recommendation"
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  Y. Jiang, C. Huang, and L. Xia
  Most Influential Papers of KDD'23 (Rank 10 / 497)
  [pdf] [code]

• [WSDM'23] "Heterogeneous Graph Contrastive Learning for Recommendation"
  ACM International Conference on Web Search and Data Mining
  M. Chen, C. Huang, L. Xia, W. Wei, Y. Xu and R. Luo
  Most Cited Paper of WSDM'23 (Rank 1 / 123)
  [pdf] [code]

• [SIGIR'22] "Hypergraph Contrastive Collaborative Filtering"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  Most Influential Papers of SIGIR'22 (Rank 3 / 161)
  L. Xia, C. Huang, Y. Xu, J. Zhao, D. Yin and J. Huang
  [pdf] [code]

• [KDD'22] "Self-Supervised Hypergraph Transformer for Recommender Systems"
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  L. Xia, C. Huang and C. Zhang
  [pdf] [code]

• [TNNLS'22] "Multi-Behavior Graph Neural Networks for Recommender System"
  IEEE Transactions on Neural Networks and Learning Systems
  L. Xia, C. Huang, Y. Xu, P. Dai and L. Bo
  [pdf] [code]

• [TKDE'22] "Multi-Behavior Sequential Recommendation with Temporal Graph Transformer"
  IEEE Transactions on Data Engineering
  L. Xia, C. Huang, Y. Xu and J. Pei
  [pdf] [code]

• [SIGIR'22] "Knowledge Graph Contrastive Learning for Recommendation"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  Most Influential Papers of SIGIR'22 (Ranked 2 / 161)
  Y. Yang, C. Huang, L. Xia and C. Li
  [pdf] [code]

• [WSDM'22] "Contrastive Meta Learning with Behavior Multiplicity for Recommendation"
  ACM International Conference on Web Search and Data Mining
  Best Paper Nomination & Most Cited Papers of WSDM'22 (Rank 3 / 159)
  W. Wei, C. Huang, L. Xia, Y. Xu, J. Zhao, D. Yin
  [pdf] [code]

• [SIGIR'21] "Graph Meta Network for Multi-Behavior Recommendation"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  Most Influential Papers of SIGIR'21 (Rank 13 / 151)
  L. Xia, Y. Xu, C. Huang, P. Dai and L. Bo
  [pdf] [code]

• [AAAI'21] "Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation"
  AAAI Conference on Artificial Intelligence
  L. Xia, C. Huang, Y. Xu, P. Dai, M. Lu and L. Bo
  [pdf] [code]

• [TOIS'21] "Collaborative Reflection-Augmented Autoencoder Network for Recommender Systems"
  ACM Transactions on Information Systems
  L. Xia, C. Huang, Y. Xu, H. Xu, X. Li and W. Zhang
  [pdf] [code]

• [ICDE'21] "Multi-Behavior Enhanced Recommendation with Cross-Interaction Collaborative Relation Modeling"
  IEEE International Conference on Data Engineering
  L. Xia, C. Huang, Y. Xu, P. Dai, M. Lu and L. Bo
  [pdf] [code]

• [IJCAI'21] "Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation Learning"
  International Joint Conference on Artificial Intelligence
  L. Xia, C. Huang, Y. Xu, P. Dai, L. Bo, X. Zhang, T. Chen
  [pdf] [code]

• [SIGIR'20] "Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  L. Xia, C. Huang, Y. Xu, P. Dai and L. Bo
  [pdf] [code]

Education Background

• South China University of Technology

  09/2017-12/2021
  Ph.D., at Department of Computer Science and Technology
• South China University of Technology

  09/2013-06/2017
  Bachelor, Majored in Computer Science and Technology (English-Taught Class)

Work Experience

• The University of Hong Kong

  11/2024-Present
  Research Assistant Professor, at School of Computing and Data Science
• The University of Hong Kong

  06/2022-Present
  Postdoctoral Fellow, at Department of Computer Science and Institute of Data Science
• Microsoft Research Asia

  09/2016-05/2017
  Research Development Intern, at Innovation Engineering Group

Services

Program Commitee Member of Conferences:

• In year 2024: SIGIR, KDD, WWW, AAAI, NeurIPS, ICLR, CIKM, SDM
• In year 2023: SIGIR, KDD, WWW, AAAI, NeurIPS
• In year 2022: KDD, AAAI

Reviewer for Journals:

• IEEE Transactions: TKDE, TBD, TNNLS, TLT
• ACM Transactions: TOIS, TWEB, TKDD, TIST
• APIN, DMKD, Neural Networks, Information Science

Presentations

• 08/2024  Tutorial on Large Language Models for Graphs at KDD'2024
• 05/2024  Tutorial on Large Language Models for Graphs at WWW'2024
• 05/2023  Spotlight Paper presentation at WWW'2023
• 05/2023  Talk at Hunan University
• 12/2022  Talk at Institute of Computing Technology, Chinese Academy of Sciences
• 10/2022  Tutorial on Self-Supervised Learning for Recommendation at CIKM'2022
• 12/2021  Talk at Guangdong University of Technology
• 11/2021  Talk at College of Future Technology, SCUT
• Research paper presentations at international conferences:
  SIGIR'2023, WWW'2023, ICDE'2023, CIKM'2023, SIGIR'2022, SIGIR'2021, ICDE'2021, SIGIR'2020

Hornors & Awards

Worlds's Top 2% Scientists 2024 published by Stanford University.

AI 2000 Most Influential Scholars (2022-2023) by Aminer in Data Mining and Information Retrieval.

One KDD 2024 Most Influential Paper (Rank 10th / 559 Accepted Papers)

One WWW 2024 Most Influential Paper (Rank 1st / 405 Accepted Papers)

Three WWW 2023 Most Influential Papers (Rank 4th, 5th, 10th / 323 Accepted Papers)

One SIGIR 2023 Most Influential Paper (Rank 12th / 165 Accepted Papers)

Two KDD 2023 Most Influential Papers (Rank 10th, 11th / 497 Accepted Papers)

Two SIGIR 2022 Most Influential Papers (Rank 2nd, 3rd / 161 Accepted Papers)

One SIGIR 2021 Most Influential Paper (Rank 13th / 151 Accepted Papers)

ACM MM 2024 Best Paper Nomination & Hornorable Mention Award

WWW 2023 Best Paper Nomination & Spotlight Paper

WSDM 2022 Best Paper Nomination & Top-3 Most Cited Paper

WSDM 2023 Top-1 Most Cited Paper

ICLR 2023 Spotlight Paper (Top 25%)