💻 Selected Research Papers

† co-first author, * corresponding author

My full paper list can also be found at Google Scholar.

ArXiv 2025 Yu Wang, Yonghui Yang, Le Wu, Yi Zhang, Richang Hong. Multimodal Large Language Models with Adaptive Preference Optimization for Sequential Recommendation. [Paper]
ArXiv 2025 Yicheng He, Chengsong Huang, Zongxia Li, Jiaxin Huang, Yonghui Yang. VisPlay: Self-Evolving Vision-Language Models from Images. [Paper]
ArXiv 2025 Yicheng He, Zhou Kaiyu, Haoyue Bai, Fengbin Zhu, Yonghui Yang *. Understanding Embedding Scaling in Collaborative Filtering. [Paper]
ArXiv 2025 Min Hou, Le Wu, Yuxin Liao, Yonghui Yang, Zhen Zhang, Changlong Zheng, Han Wu, Richang Hong. A Survey on Generative Recommendation: Data, Model, and Tasks. [Paper]
ArXiv 2025 Yonghui Yang, Le Wu, Zhuangzhuang He, Zhengwei Wu, Richang Hong, Meng Wang. Less is More: Information Bottleneck Denoised Multimedia Recommendation. [Paper]

AAAI 2026 Jilong Liu, Pengyang Shao, Wei Qin, Fei Liu, Yonghui Yang, Richang Hong. Debate over Mixed-knowledge: A Robust Multi-Agent Framework for Incomplete Knowledge Graph Question Answering. [Paper] [Code]
SIGIR 2025 Yonghui Yang, Le Wu, Yuxin Liao, Zhuangzhuang He, Pengyang shao, Richang Hong, Meng Wang. Invariance Matters: Empowering Social Recommendation via Graph Invariant Learning. [Paper] [Code]
SIGIR 2025 Yuxin Liao, Yonghui Yang, Min Hou, Le Wu, Hefei Xu, Hao Liu. Mitigating Distribution Shifts in Sequential Recommendation: An Invariance Perspective.

IEEE TKDE Zihan Wang, Yonghui Yang *, Le Wu *, Richang Hong, Meng Wang. Making Non-overlapping Matters: An Unsupervised Alignment enhanced Cross-Domain Cold-Start Recommendation.[Paper] [Code]
KDD 2025 Pengyang Shao†, Yonghui Yang†, Chen Gao, Lei Chen, Kun Zhang, Chenyi Zhuang, Le Wu, Meng Wang. Exploring Heterogeneity and Uncertainty for Graph-based Cognitive Diagnosis Models in Intelligent Education. [Paper] [Code]
KDD 2024 Yonghui Yang, Le Wu, Zihan Wang, Zhuangzhuang He, Richang Hong, Meng Wang. Graph Bottlenecked Social Recommendation. [Paper] [Code]
IJCAI 2024 Junsong Xie†, Yonghui Yang†, Zihan Wang, Le Wu. Learning Fair Representations for Recommendation via Information Bottleneck Principle. [Paper] [Code]

IEEE TKDE Yonghui Yang, Le Wu, Kun Zhang, Richang Hong, Hailin Zhou, Zhiqiang Zhang, Jun Zhou, Meng Wang. Hyperbolic Graph Learning for Social Recommendation. [Paper] [Code]
SIGIR 2023 Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang. Generative-Contrastive Graph Learning for Recommendation. [Paper] [Code]

SIGIR 2021 Yonghui Yang, Le Wu, Richang Hong, Kun Zhang, Meng Wang. Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization. [Paper] [Code]

SIGIR 2020 Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Yanjie Fu, Meng Wang. Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach. [Paper] [Code]
SIGIR 2020 Le Wu, Yonghui Yang, Lei Chen, Richang Hong, Meng Wang. Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation. [Paper]