Publications

2025

1. WSDM

   Tutorial: Towards Secure and Robust Recommender Systems: A Data-Centric Perspective

   Zongwei Wang, Junliang Yu, Tong Chen, Hongzhi Yin, Shazia Sadiq, and Min Gao

   The 18th ACM International Conference on Web Search and Data Mining, 2025

   Code Website

2024

1. KDD

   Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks

   Zongwei Wang, Junliang Yu, Min Gao, Hongzhi Yin, Bin Cui, and Shazia Sadiq

   Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2024

   PDF Code
2. KDD

   Consistency and Discrepancy-Based Contrastive Tripartite Graph Learning for Recommendations

   Linxin Guo, Yaochen Zhu, Min Gao, Yinghui Tao, Junliang Yu, and Chen Chen

   Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2024

   PDF Code
3. WWW

   Prompt-enhanced Federated Content Representation Learning for Cross-domain Recommendation

   Lei Guo, Ziang Lu, Junliang Yu, Nguyen Quoc Viet Hung, and Hongzhi Yin

   Proceedings of the Web Conference, 2024

   PDF Code
4. ICDE

   Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation

   Xinyi Gao, Wentao Zhang, Junliang Yu, Yingxia Shao, Nguyen Quoc Viet Hung, Bin Cui, and 1 more author

   IEEE International Conference on Data Engineering, 2024

   PDF
5. WSDM

   Motif-based Prompt Learning for Universal Cross-domain Recommendation

   Bowen Hao, Chaoqun Yang, Lei Guo, Junliang Yu, and Hongzhi Yin

   The 17th ACM International Conference Web Search and Data Mining, 2024

   PDF
6. arXiv

   Poisoning Attacks against Recommender Systems: A Survey

   Zongwei Wang, Min Gao, Junliang Yu, Hao Ma, Hongzhi Yin, and Shazia Sadiq

   arXiv preprint arXiv:2401.01527, 2024

   PDF Code
7. arXiv

   LLM-Powered Text Simulation Attack Against ID-Free Recommender Systems

   Zongwei Wang, Min Gao, Junliang Yu, Xinyi Gao, Quoc Viet Hung Nguyen, Shazia Sadiq, and 1 more author

   arXiv preprint arXiv:2405.13707, 2024

   PDF
8. arXiv

   Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition

   Xinyi Gao, Tong Chen, Wentao Zhang, Junliang Yu, Guanhua Ye, Quoc Viet Hung Nguyen, and 1 more author

   arXiv preprint arXiv:2405.13707, 2024

   PDF
9. arXiv

   Graph Condensation: A Survey

   Xinyi Gao, Junliang Yu, Wei Jiang, Tong Chen, Wentao Zhang, Bin Cui, and 1 more author

   arXiv preprint arXiv:2401.11720, 2024

   PDF
10. arXiv

    A Survey on Point-of-Interest Recommendation: Models, Architectures, and Security

    Qianru Zhang, Peng Yang, Junliang Yu, Haixin Wang, Xingwei He, Siu-Ming Yiu, and 1 more author

    arXiv preprint arXiv:2410.02191, 2024

    PDF

2023

1. TKDE

   XSimGCL: Towards extremely simple graph contrastive learning for recommendation

   Junliang Yu, Xin Xia, Tong Chen, Lizhen Cui, Nguyen Quoc Viet Hung, and Hongzhi Yin

   IEEE Transactions on Knowledge and Data Engineering, 2023

   ESI Highly Cited Paper

   PDF Code
2. DASFAA

   Tutorial: Self-Supervised Learning for Recommendation: Foundations, Methods and Prospects

   Junliang Yu, Tong Chen, and Hongzhi Yin

   Proceedings of the 28th International Conference on Database Systems for Advanced Applications, 2023

   PDF
3. CIKM

   Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation

   Xin Xia, Junliang Yu, Guandong Xu, and Hongzhi Yin

   Proceedings of the 32nd ACM international conference on information and knowledge management, 2023

   PDF Code
4. CIKM

   Semantic-aware Node Synthesis for Imbalanced Heterogeneous Information Networks

   Xinyi Gao, Wentao Zhang, Tong Chen, Junliang Yu, Quoc Viet Hung Nguyen, and Hongzhi Yin

   Proceedings of the 32nd ACM international conference on information and knowledge management, 2023

   PDF Code
5. KDD

   Efficient Bi-Level Optimization for Recommendation Denoising

   Zongwei Wang, Min Gao, Wentao Li, Junliang Yu, Linxin Guo, and Hongzhi Yin

   Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2023

   PDF Code

2022

1. SIGIR

   Are graph augmentations necessary? simple graph contrastive learning for recommendation

   Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Lizhen Cui, and Quoc Viet Hung Nguyen

   Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022

   The most cited paper in SIGIR’22, applied in Tencent Music

   PDF Code
2. TKDE

   Self-supervised learning for recommender systems: A survey

   Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Jundong Li, and Zi Huang

   IEEE Transactions on Knowledge and Data Engineering, 2022

   ESI Hot and Highly Cited Paper

   PDF Code
3. WWW

   Tutorial: Self-supervised learning in recommendation: fundamentals and advances

   Junliang Yu, Tong Chen, and Hongzhi Yin

   Companion Proceedings of the Web Conference, 2022

   Website
4. TOIS

   Efficient on-device session-based recommendation

   Xin Xia, Junliang Yu, Qinyong Wang, Chaoqun Yang, Quoc Viet Hung Nguyen, and Hongzhi Yin

   ACM Transactions on Information Systems (TOIS), 2022

   PDF Code
5. SIGIR

   On-device next-item recommendation with self-supervised knowledge distillation

   Xin Xia, Hongzhi Yin, Junliang Yu, Qinyong Wang, Guandong Xu, and Quoc Viet Hung Nguyen

   Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022

   PDF Code
6. VLDBJ

   Fast-adapting and privacy-preserving federated recommender system

   Qinyong Wang, Hongzhi Yin, Tong Chen, Junliang Yu, Alexander Zhou, and Xiangliang Zhang

   The VLDB Journal, 2022

   PDF Code

2021

1. KDD

   Socially-aware self-supervised tri-training for recommendation

   Junliang Yu, Hongzhi Yin, Min Gao, Xin Xia, Xiangliang Zhang, and Nguyen Quoc Viet Hung

   Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021

   One of the most influential papers in KDD’21

   PDF Code
2. WWW

   Self-supervised multi-channel hypergraph convolutional network for social recommendation

   Junliang Yu, Hongzhi Yin, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung, and Xiangliang Zhang

   Proceedings of the Web Conference, 2021

   The 2nd most cited paper in WWW’21

   PDF Code
3. AAAI

   Self-supervised hypergraph convolutional networks for session-based recommendation

   Xin Xia, Hongzhi Yin, Junliang Yu, Qinyong Wang, Lizhen Cui, and Xiangliang Zhang

   Proceedings of the AAAI conference on artificial intelligence, 2021

   One of the most influential papers in AAAI’21

   PDF Code
4. CIKM

   Self-supervised graph co-training for session-based recommendation

   Xin Xia, Hongzhi Yin, Junliang Yu, Yingxia Shao, and Lizhen Cui

   Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021

   One of the most influential papers in CIKM’21

   PDF Code
5. CIKM

   Double-scale self-supervised hypergraph learning for group recommendation

   Junwei Zhang, Min Gao, Junliang Yu, Lei Guo, Jundong Li, and Hongzhi Yin

   Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021

   PDF Code

2020

1. TKDE

   Enhancing social recommendation with adversarial graph convolutional networks

   Junliang Yu, Hongzhi Yin, Jundong Li, Min Gao, Zi Huang, and Lizhen Cui

   IEEE Transactions on Knowledge and Data Engineering, 2020

   ESI Highly Cited Paper

   PDF Code

2019

1. ICDM

   Generating reliable friends via adversarial training to improve social recommendation

   Junliang Yu, Min Gao, Hongzhi Yin, Jundong Li, Chongming Gao, and Qinyong Wang

   IEEE International Conference on Data Mining (ICDM), 2019

   PDF Code

2018

1. CIKM

   Adaptive implicit friends identification over heterogeneous network for social recommendation

   Junliang Yu, Min Gao, Jundong Li, Hongzhi Yin, and Huan Liu

   Proceedings of the 27th ACM international conference on information and knowledge management, 2018

   PDF Code