Publications (Full List)

In Year 2024

• [NeurIPS'24] "GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks"
  Advances in Neural Information Processing Systems
  Z. Li, L. Xia, Y. Xu and C. Huang
  [pdf] [code]

• [WWW'24] "GraphPro: Graph Pre-training and Prompt Learning for Recommendation"
  ACM The Web Conference
  Y. Yang, L. Xia, D. Luo, K. Lin and C. Huang
  [pdf] [code]

• [WSDM'24] "SSLRec: A Self-Supervised Learning Framework for Recommendation"
  ACM International Conference on Recommender Systems
  X. Ren, L. Xia, Y. Yang, W. Wei, T. Wang, X. Cai and C. Huang
  [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
  [pdf] [code]

• [WSDM'24] "DiffKG: Knowledge Graph Diffusion Model for Recommendation"
  ACM International Conference on Web Search and Data Mining
  Y. Jiang, Y. Yang, L. Xia and C. Huang
  [pdf] [code]

In Year 2023

• [WWW'23] "Automated Self-Supervised Learning for Recommendation"
  ACM The Web Conference
  Spotlight Paper & Best Paper Nominations (Acceptance Rate 16 / 365 = 4.4%)
  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
  Top-5 Most-Cited Paper in WWW'23 (Acceptance Rate 5 / 323 = 1.5%)
  [pdf] [code]

• [WWW'23] "Multi-Modal Self-Supervised Learning for Recommendation"
  ACM The Web Conference
  W. Wei, C. Huang, L. Xia and C. Zhang
  Featured in Most Influential Paper in WWW'23 (Ranked 3rd)
  [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]

• [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
  Top-3 Most-Cited Paper in WSDM'23 (Acceptance Rate 3 / 123 = 2.4%)
  [pdf] [code]

• [ICML'23] "Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation"
  International Conference on Machine Learning
  Q. Zhang, C. Huang, L. Xia, Z. Wang, S.M. Yiu and R. Han
  [pdf] [code]

• [SIGIR'23] "Graph Transformer for Recommendation"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  C. Li, L. Xia, X. Ren, Y. Ye, Y. Xu and C. Huang
  [pdf] [code]

• [SIGIR'23] "Disentangled Contrastive Collaborative Filtering"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  X. Ren, L. Xia, J. Zhao, D. Yin and C. Huang
  [pdf] [code]

• [SIGIR'23] "Graph Masked Autoencoder for Sequential Recommendation"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  Y. Ye, L. Xia and C. Huang
  [pdf] [code]

• [IJCAI'23] "Denoised Self-Augmented Learning for Social Recommendation"
  International Joint Conference on Artificial Intelligence
  T. Wang, L. Xia and C. Huang
  [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.Z. Huang
  [pdf] [code]

• [KDD'23] "Adaptive Graph Contrastive Learning for Recommendation"
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  Y. Jiang, C. Huang, L. Xia
  [pdf] [code]

• [WWW'23] "Automated Spatio-Temporal Graph Contrastive Learning"
  ACM The Web Conference
  Q. Zhang, C. Huang, L. Xia, Z. Wang, Z. Li and S. Yiu
  [pdf] [code]

• [CIKM'23] "Explainable Spatio-Temporal Graph Neural Networks"
  ACM International Conference on Information and Knowledge Management
  J. Tang, L. Xia and C. Huang
  [pdf] [code]

• [CIKM'23] "Spatio-Temporal Meta Contrastive Learning"
  ACM International Conference on Information and Knowledge Management
  J. Tang, L. Xia, J. Hu and C. Huang
  [pdf] [code]

• [CIKM'23] "How Expressive are Graph Neural Networks in Recommendation?"
  ACM International Conference on Information and Knowledge Management
  X. Cai, L. Xia, X. Ren and C. Huang
  [pdf] [code]

• [Recsys'23] "Multi-Relational Contrastive Learning for Recommendation"
  ACM International Conference on Recommender Systems
  W. Wei, L. Xia and C. Huang
  [pdf] [code]

In Year 2022

• [SIGIR'22] "Hypergraph Contrastive Collaborative Filtering"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  Featured in Most Influential Papers in SIGIR'22 (Ranked 2nd)
  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
  Featured in Most Influential Papers of SIGIR'22 (Ranked 3rd)
  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 Candidate & Top-2 Most Cited Paper among All 159 Papers
  W. Wei, C. Huang, L. Xia, Y. Xu, J. Zhao, D. Yin
  [pdf] [code]

• [KDD'22] "Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation"
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  Y. Yang, C. Huang, L. Xia, Y. Liang, Y. Yu and C. Li
  [pdf] [code]

• [ICDE'22] "Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction"
  IEEE International Conference on Data Engineering
  Z. Li, C. Huang, L. Xia, Y. Xu and J. Pei
  [pdf] [code]

In Year 2021

• [SIGIR'21] "Graph Meta Network for Multi-Behavior Recommendation"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  Top-10 Most Cited Papers in SIGIR'21 (Acceptance Rate 10 / 152 = 6.6%)
  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]

• [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]

• [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]

• [AAAI'21] "Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation"
  AAAI Conference on Artificial Intelligence
  C. Huang, J. Chen, L. Xia, Y. Xu, P. Dai, Y. Chen, L. Bo, J. Zhao and J. Huang
  [pdf] [code]

• [AAAI'21] "Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network"
  AAAI Conference on Artificial Intelligence
  X. Zhang, C. Huang, Y. Xu, L. Xia, P Dai, L. Bo, J. Zhang and Y. Zheng
  [pdf] [code]

• [AAAI'21] "Knowledge-aware Coupled Graph Neural Network for Social Recommendation"
  AAAI Conference on Artificial Intelligence
  C. Huang, H. Xu, Y. Xu, P. Dai, L. Xia, M. Lu, L. Bo, H. Xing, X. Lai, Y. Ye
  [pdf] [code]

• [CIKM'21] "Social Recommendation with Self-Supervised Metagraph Informax Network"
  ACM International Conference on Information and Knowledge Management
  X. Long, C. Huang, Y. Xu, H. Xu, P. Dai, L. Xia, L. Bo
  [pdf] [code]

In Year 2020

• [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]

• [ICDM'20] "Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks"
  IEEE International Conference on Data Mining
  H. Xu, C. Huang, Y. Xu, L. Xia, H. Xing and D. Yin
  [pdf] [code]

• [CIKM'20] "Spatial-Temporal Convolutional Graph Attention Networks for Citywide Traffic Flow Forecasting"
  ACM International Conference on Information and Knowledge Management
  X. Zhang, C. Huang, Y. Yu, and L. Xia
  [pdf] [code]