Inter- and Intra-Domain Relation-Aware Heterogeneous Graph Convolutional Networks for Cross-Domain Recommendation. - Ke Wang 038; Yanmin Zhu 006; Haobing Liu 001; Tianzi Zang; Chunyang Wang 001; Kuan Liu (DASFAA (2), 2022)

Disentangled Contrastive Learning for Cross-Domain Recommendation. - Ruohan Zhang; Tianzi Zang; Yanmin Zhu 006; Chunyang Wang 001; Ke Wang 038; Jiadi Yu (DASFAA (2), 2023)

Rating-Review Graph Contrastive Learning for Review-based Recommendation. - Jiacheng Shi; Yanmin Zhu 006; Ke Wang 038; Mengyuan Jing; Tianzi Zang; Jiadi Yu; Feilong Tang (ICPADS, 2023)

A Preference Learning Decoupling Framework for User Cold-Start Recommendation. - Chunyang Wang 001; Yanmin Zhu 006; Aixin Sun; Zhaobo Wang; Ke Wang 038 (SIGIR, 2023)

Learning Aspect-Aware High-Order Representations from Ratings and Reviews for Recommendation. - Ke Wang 038; Yanmin Zhu 006; Haobing Liu 001; Tianzi Zang; Chunyang Wang 001 (ACM Trans. Knowl. Discov. Data, 2023)

Multifaceted Relation-aware Meta-learning with Dual Customization for User Cold-start Recommendation. - Chunyang Wang 001; Yanmin Zhu 006; Haobing Liu 001; Tianzi Zang; Ke Wang 038; Jiadi Yu (ACM Trans. Knowl. Discov. Data, 2023)

Review-Enhanced Hierarchical Contrastive Learning for Recommendation. - Ke Wang 038; Yanmin Zhu 006; Tianzi Zang; Chunyang Wang 001; Mengyuan Jing (AAAI, 2024)

Contrastive Self-supervised Learning in Recommender Systems: A Survey. - Mengyuan Jing; Yanmin Zhu 006; Tianzi Zang; Ke Wang 038 (ACM Trans. Inf. Syst., 2024)

Multi-aspect Graph Contrastive Learning for Review-enhanced Recommendation. - Ke Wang 038; Yanmin Zhu 006; Tianzi Zang; Chunyang Wang 001; Kuan Liu; Peibo Ma (ACM Trans. Inf. Syst., 2024)

Contrastive Multi-view Interest Learning for Cross-domain Sequential Recommendation. - Tianzi Zang; Yanmin Zhu 006; Ruohan Zhang; Chunyang Wang 001; Ke Wang 038; Jiadi Yu (ACM Trans. Inf. Syst., 2024)

Enhancing Cross-Domain Recommendation with Plug-In Contrastive Representations from Large Language Models. - Ke Wang 038; Ji Zhang; Kuan Liu (SIGIR, 2025)