Yonghui Yang

Yonghui Yang

Hefei University of Technology (HFUT)

💻 Selected Research Papers

† co-first author, * corresponding author

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

MLLM Safety and Alignment

  • CVPR 2026 Yicheng He, Chengsong Huang, Zongxia Li, Jiaxin Huang, Yonghui Yang. VisPlay: Self-Evolving Vision-Language Models from Images. [Paper]
  • ArXiv 2026 Yonghui Yang, Wenjian Tao, Jilong Liu, Xingyu Zhu, Junfeng Fang, Weibiao Huang, Le Wu, Richang Hong, Tat-Sent Chua. Revisiting Robustness for LLM Safety Alignment via Selective Geometry Control. [Paper]
  • ArXiv 2026 Yonghui Yang, Junwei Li, Jilong Liu, Yicheng He, Fengbin Zhu, Weibiao Huang, Le Wu, Richang Hong, Tat-Seng Chua. Controllable Value Alignment in Large Language Models through Neuron-Level Editing. [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]

Trustworthy Recommendation

  • ArXiv 2025 Yonghui Yang, Le Wu, Zhuangzhuang He, Zhengwei Wu, Richang Hong, Meng Wang. Less is More: Information Bottleneck Denoised Multimedia Recommendation. [Paper]
  • 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.
  • 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]

Data-Centric Recommendation

  • 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 Yu Wang, Yonghui Yang, Le Wu, Yi Zhang, Richang Hong. Multimodal Large Language Models with Adaptive Preference Optimization for Sequential Recommendation. [Paper]
  • TMLR 2025 Yicheng He, Zhou Kaiyu, Haoyue Bai, Fengbin Zhu, Yonghui Yang *. Understanding Embedding Scaling in Collaborative Filtering. [Paper]
  • TKDE 2025 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]
  • TKDE 2024 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]