Collaborative Shilling Detection Bridging Factorization and User Embedding. - Tong Dou; Junliang Yu; Qingyu Xiong; Min Gao 001; Yuqi Song; Qianqi Fang (CollaborateCom, 2017)

PUED: A Social Spammer Detection Method Based on PU Learning and Ensemble Learning. - Yuqi Song; Min Gao 001; Junliang Yu; Wentao Li 001; Lulan Yu; Xinyu Xiao (CollaborateCom, 2017)

Integrating User Embedding and Collaborative Filtering for Social Recommendations. - Junliang Yu; Min Gao 001; Yuqi Song; Qianqi Fang; Wenge Rong; Qingyu Xiong (CollaborateCom, 2017)

Impact of the Important Users on Social Recommendation System. - Zehua Zhao; Min Gao 001; Junliang Yu; Yuqi Song; Xinyi Wang 008; Min Zhang (CollaborateCom, 2017)

PUD: Social Spammer Detection Based on PU Learning. - Yuqi Song; Min Gao 001; Junliang Yu; Wentao Li 001; Junhao Wen 001; Qingyu Xiong (ICONIP (5), 2017)

Make Users and Preferred Items Closer: Recommendation via Distance Metric Learning. - Junliang Yu; Min Gao 001; Wenge Rong; Yuqi Song; Qianqi Fang; Qingyu Xiong (ICONIP (5), 2017)

Connecting Factorization and Distance Metric Learning for Social Recommendations. - Junliang Yu; Min Gao 001; Yuqi Song; Zehua Zhao; Wenge Rong; Qingyu Xiong (KSEM, 2017)

A Social Recommender Based on Factorization and Distance Metric Learning. - Junliang Yu; Min Gao 001; Wenge Rong; Yuqi Song; Qingyu Xiong (IEEE Access, 2017)

Adaptive Implicit Friends Identification over Heterogeneous Network for Social Recommendation. - Junliang Yu; Min Gao 001; Jundong Li; Hongzhi Yin; Huan Liu 001 (CIKM, 2018)

Meta-path Based Heterogeneous Graph Embedding for Music Recommendation. - Qianqi Fang; Ling Liu 001; Junliang Yu; Junhao Wen 001 (ICONIP (3), 2018)

Social Recommendation Based on Implicit Friends Discovering Via Meta-Path. - Yuqi Song; Min Gao 001; Junliang Yu; Qingyu Xiong (ICTAI, 2018)

Detection of Shilling Attack Based on Bayesian Model and User Embedding. - Fan Yang; Min Gao 001; Junliang Yu; Yuqi Song; Xinyi Wang 008 (ICTAI, 2018)

融合矩阵分解与距离度量学习的社会化推荐算法 (Social Recommendation Method Integrating Matrix Factorization and Distance Metric Learning). - Junhao Wen 001; Dawen Dai; Junliang Yu; Min Gao 001; Yihao Zhang 002 (计算机科学, 2018)

Generating Reliable Friends via Adversarial Training to Improve Social Recommendation. - Junliang Yu; Min Gao 001; Hongzhi Yin; Jundong Li; Chongming Gao; Qinyong Wang (ICDM, 2019)

Nonlinear Transformation for Multiple Auxiliary Information in Music Recommendation. - Junwei Zhang 004; Min Gao 001; Junliang Yu; Xinyi Wang 008; Yuqi Song; Qingyu Xiong (IJCNN, 2019)

A Minimax Game for Generative and Discriminative Sample Models for Recommendation. - Zongwei Wang 002; Min Gao 001; Xinyi Wang 008; Junliang Yu; Junhao Wen 001; Qingyu Xiong (PAKDD (2), 2019)

Enhance Social Recommendation with Adversarial Graph Convolutional Networks. - Junliang Yu; Hongzhi Yin; Jundong Li; Min Gao 001; Zi Huang; Lizhen Cui (CoRR, 2020)

Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. - Xin Xia 013; Hongzhi Yin; Junliang Yu; Qinyong Wang; Lizhen Cui; Xiangliang Zhang 001 (AAAI, 2021)

Self-Supervised Graph Co-Training for Session-based Recommendation. - Xin Xia 013; Hongzhi Yin; Junliang Yu; Yingxia Shao; Lizhen Cui (CIKM, 2021)

Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation. - Junwei Zhang 004; Min Gao 001; Junliang Yu; Lei Guo 008; Jundong Li; Hongzhi Yin (CIKM, 2021)

Socially-Aware Self-Supervised Tri-Training for Recommendation. - Junliang Yu; Hongzhi Yin; Min Gao 001; Xin Xia 013; Xiangliang Zhang 001; Nguyen Quoc Viet Hung (KDD, 2021)

Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. - Junliang Yu; Hongzhi Yin; Jundong Li; Qinyong Wang; Nguyen Quoc Viet Hung; Xiangliang Zhang 001 (WWW, 2021)

Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack. - Fan Wu; Min Gao 001; Junliang Yu; Zongwei Wang 002; Kecheng Liu; Wange Xu (CoRR, 2021)

Graph Augmentation-Free Contrastive Learning for Recommendation. - Junliang Yu; Hongzhi Yin; Xin Xia 013; Lizhen Cui; Quoc Viet Hung Nguyen (CoRR, 2021)

Path-based reasoning over heterogeneous networks for recommendation via bidirectional modeling. - Junwei Zhang 004; Min Gao 001; Junliang Yu; Linda Yang 002; Zongwei Wang 002; Qingyu Xiong (Neurocomputing, 2021)

Recommender systems based on generative adversarial networks: A problem-driven perspective. - Min Gao 001; Junwei Zhang 004; Junliang Yu; Jundong Li; Junhao Wen 001; Qingyu Xiong (Inf. Sci., 2021)

Ready for emerging threats to recommender systems? A graph convolution-based generative shilling attack. - Fan Wu; Min Gao 001; Junliang Yu; Zongwei Wang 002; Kecheng Liu; Xu Wang (Inf. Sci., 2021)

On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation. - Xin Xia 013; Hongzhi Yin; Junliang Yu; Qinyong Wang; Guandong Xu; Quoc Viet Hung Nguyen (SIGIR, 2022)

Are Graph Augmentations Necessary?: Simple Graph Contrastive Learning for Recommendation. - Junliang Yu; Hongzhi Yin; Xin Xia 013; Tong Chen 005; Lizhen Cui; Quoc Viet Hung Nguyen (SIGIR, 2022)

Accepted Tutorials at The Web Conference 2022. - Riccardo Tommasini 001; Senjuti Basu Roy; Xuan Wang 008; Hongwei Wang; Heng Ji 001; Jiawei Han 001; Preslav Nakov; Giovanni Da San Martino; Firoj Alam; Markus Schedl; Elisabeth Lex; Akash Bharadwaj; et al. (WWW (Companion Volume), 2022)

Addressing the Extreme Cold-Start Problem in Group Recommendation. - Linxin Guo; Yinghui Tao; Min Gao 001; Junliang Yu; Liang Zhao; Wentao Li 001 (CoRR, 2022)

Enhancing Social Recommendation With Adversarial Graph Convolutional Networks. - Junliang Yu; Hongzhi Yin; Jundong Li; Min Gao 001; Zi Huang; Lizhen Cui (IEEE Trans. Knowl. Data Eng., 2022)

Fast-adapting and privacy-preserving federated recommender system. - Qinyong Wang; Hongzhi Yin; Tong Chen 005; Junliang Yu; Alexander Zhou 001; Xiangliang Zhang 001 (VLDB J., 2022)

Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation. - Xin Xia 013; Junliang Yu; Guandong Xu; Hongzhi Yin (CIKM, 2023)

Semantic-aware Node Synthesis for Imbalanced Heterogeneous Information Networks. - Xinyi Gao 001; Wentao Zhang 001; Tong Chen 005; Junliang Yu; Nguyen Quoc Viet Hung; Hongzhi Yin (CIKM, 2023)

Efficient Bi-Level Optimization for Recommendation Denoising. - Zongwei Wang 002; Min Gao 001; Wentao Li 001; Junliang Yu; Linxin Guo; Hongzhi Yin (KDD, 2023)

Poisoning Attacks Against Contrastive Recommender Systems. - Zongwei Wang 002; Junliang Yu; Min Gao 001; Hongzhi Yin; Bin Cui 001; Shazia Sadiq (CoRR, 2023)

Enhancing recommender systems with self-supervised learning - Junliang Yu (2023)

Who are the Best Adopters? User Selection Model for Free Trial Item Promotion. - Shiqi Wang 018; Chongming Gao; Min Gao 001; Junliang Yu; Zongwei Wang 002; Hongzhi Yin (IEEE Trans. Big Data, 2023)

Predictive and Contrastive: Dual-Auxiliary Learning for Recommendation. - Yinghui Tao; Min Gao 001; Junliang Yu; Zongwei Wang 002; Qingyu Xiong; Xu Wang (IEEE Trans. Comput. Soc. Syst., 2023)

Efficient On-Device Session-Based Recommendation. - Xin Xia 013; Junliang Yu; Qinyong Wang; Chaoqun Yang 002; Nguyen Quoc Viet Hung; Hongzhi Yin (ACM Trans. Inf. Syst., 2023)

Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation. - Xinyi Gao 001; Wentao Zhang 001; Junliang Yu; Yingxia Shao; Quoc Viet Hung Nguyen; Bin Cui 001; Hongzhi Yin (ICDE, 2024)

Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks. - Zongwei Wang 002; Junliang Yu; Min Gao 001; Hongzhi Yin; Bin Cui 001; Shazia Sadiq (KDD, 2024)

Consistency and Discrepancy-Based Contrastive Tripartite Graph Learning for Recommendations. - Linxin Guo; Yaochen Zhu; Min Gao 001; Yinghui Tao; Junliang Yu; Chen Chen 022 (KDD, 2024)

Motif-based Prompt Learning for Universal Cross-domain Recommendation. - Bowen Hao; Chaoqun Yang 002; Lei Guo 008; Junliang Yu; Hongzhi Yin (WSDM, 2024)

Prompt-enhanced Federated Content Representation Learning for Cross-domain Recommendation. - Lei Guo 008; Ziang Lu; Junliang Yu; Quoc Viet Hung Nguyen; Hongzhi Yin (WWW, 2024)

Poisoning Attacks against Recommender Systems: A Survey. - Zongwei Wang 002; Min Gao 001; Junliang Yu; Hao Ma; Hongzhi Yin; Shazia Sadiq (CoRR, 2024)

Graph Condensation: A Survey. - Xinyi Gao 001; Junliang Yu; Wei Jiang 006; Tong Chen 005; Wentao Zhang 001; Hongzhi Yin (CoRR, 2024)

Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition. - Xinyi Gao 001; Tong Chen 005; Wentao Zhang 001; Junliang Yu; Guanhua Ye; Quoc Viet Hung Nguyen; Hongzhi Yin (CoRR, 2024)

Poisoning Attacks and Defenses in Recommender Systems: A Survey. - Zongwei Wang 002; Junliang Yu; Min Gao 001; Wei Yuan 003; Guanhua Ye; Shazia Sadiq; Hongzhi Yin (CoRR, 2024)

LLM-Powered Text Simulation Attack Against ID-Free Recommender Systems. - Zongwei Wang 002; Min Gao 001; Junliang Yu; Xinyi Gao 001; Quoc Viet Hung Nguyen; Shazia Sadiq; Hongzhi Yin (CoRR, 2024)

Self-Supervised Learning for Recommender Systems: A Survey. - Junliang Yu; Hongzhi Yin; Xin Xia 013; Tong Chen 005; Jundong Li; Zi Huang (IEEE Trans. Knowl. Data Eng., 2024)

XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation. - Junliang Yu; Xin Xia 013; Tong Chen 005; Lizhen Cui; Nguyen Quoc Viet Hung; Hongzhi Yin (IEEE Trans. Knowl. Data Eng., 2024)

ID-Free Not Risk-Free: LLM-Powered Agents Unveil Risks in ID-Free Recommender Systems. - Zongwei Wang 002; Min Gao 001; Junliang Yu; Xinyi Gao 001; Quoc Viet Hung Nguyen; Shazia Sadiq; Hongzhi Yin (SIGIR, 2025)

Diversity-aware Dual-promotion Poisoning Attack on Sequential Recommendation. - Yuchuan Zhao; Tong Chen 005; Junliang Yu; Kai Zheng 001; Lizhen Cui; Hongzhi Yin (SIGIR, 2025)

Towards Secure and Robust Recommender Systems: A Data-Centric Perspective. - Zongwei Wang 002; Junliang Yu; Tong Chen 005; Hongzhi Yin; Shazia Sadiq; Min Gao 001 (WSDM, 2025)

Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition. - Xinyi Gao 001; Guanhua Ye; Tong Chen 005; Wentao Zhang 001; Junliang Yu; Hongzhi Yin (WWW, 2025)

Graph Condensation: Foundations, Methods and Prospects. - Hongzhi Yin; Xinyi Gao 001; Junliang Yu; Ruihong Qiu; Tong Chen 005; Quoc Viet Hung Nguyen; Zi Huang (WWW (Companion Volume), 2025)

BiasNavi: LLM-Empowered Data Bias Management. - Junliang Yu; Jay Thai Duong Huynh; Shaoyang Fan; Gianluca Demartini; Tong Chen 005; Hongzhi Yin; Shazia Sadiq (WWW (Companion Volume), 2025)

RuleAgent: Discovering Rules for Recommendation Denoising with Autonomous Language Agents. - Zongwei Wang 002; Min Gao 001; Junliang Yu; Yupeng Hou; Shazia Sadiq; Hongzhi Yin (CoRR, 2025)

Graph Condensation: A Survey. - Xinyi Gao 001; Junliang Yu; Tong Chen 005; Guanhua Ye; Wentao Zhang 001; Hongzhi Yin (IEEE Trans. Knowl. Data Eng., 2025)

A Survey on Point-of-Interest Recommendation: Models, Architectures, and Security. - Qianru Zhang; Peng Yang 016; Junliang Yu; Haixin Wang 003; Xingwei He 003; Siu-Ming Yiu; Hongzhi Yin (IEEE Trans. Knowl. Data Eng., 2025)

When Graph Contrastive Learning Backfires: Spectral Vulnerability and Defense in Recommendation. - Zongwei Wang 002; Min Gao 001; Junliang Yu; Shazia Sadiq; Hongzhi Yin; Ling Liu 001 (CoRR, 2025)

Controllable and Stealthy Shilling Attacks via Dispersive Latent Diffusion. - Shutong Qiao; Wei Yuan 003; Junliang Yu; Tong Chen 005; Quoc Viet Hung Nguyen; Hongzhi Yin (CoRR, 2025)