Zhiying Deng

Zhiying Deng

Lecture, National Engineering Research Center of Educational Big Data, Faculty of Artificial Intelligence in Education, Central China Normal University

About Me

I am a lecture of Central China Normal University. I graduated from School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan China, with a doctor’s degree, advised by Jianjun Li. My research interests include recommender systems, user behavior analysis, and smart education. I have served as a PC member for conferences and journals including NeurIPS, ICML, SIGIR, KDD, ACM MM, AAAI, RecSys, DASFAA, TKDE and BDMA, etc.

My research interest includes:

  • Recommendation System
  • User behavior analysis
  • Smart Education

📝 Publications

  • Zhiying Deng, Jianjun Li, Wei Liu, Juan Zhao. Unbiased Interest Modeling in Sequential Basket Analysis: Addressing Repetition Bias with Multi-Factor Estimation. 2025, 3(4): 1-27. TORS. [link]

  • Zhiying Deng, Jianjun Li, Zhiqiang Guo, Wei Liu, Li Zou, Guohui Li. Multi-view Multi-aspect Neural Networks for Next-basket Recommendation. SIGIR 2023. [link]

  • Zhiying Deng, Jianjun Li, Zhiqiang Guo, Guohui Li. Multi-aspect Interest Neighbor-augmented Network for Next-basket Recommendation. ICASSP 2023. [link]

  • Zhiying Deng, Jianjun Li, Li Zou, Wei Liu, Si Shi, Qian Chen, Juan Zhao, Guohui Li. Multi-scale Context-aware User Interest Learning for Behavior Pattern Modeling. DASFAA 2024. [link]

  • Wei Liu, Zhiying Deng, Zhongyu Niu, Jun Wang, Haozhao Wang, Zhigang Zeng, Ruixuan Li. Breaking Free from MMI: A New Frontier in Rationalization by Probing Input Utilization. ICLR 2025. [link]

  • Wei Liu, Zhiying Deng, Zhongyu Niu, Jun Wang, Haozhao Wang, Ruixuan Li. Exploring Practical Gaps in Using Cross Entropy to Implement Maximum Mutual Information Criterion for Rationalization. 2025, TACL. (to appear)

  • Wei Liu, Zhongyu Niu, Lang Gao, Zhiying Deng, Jun Wang, Haozhao Wang, Ruixuan Li. Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets. ICML 2025. [link]

  • Bin Ruan, Hao Liu, Yitian Tu, Zhiying Deng, Zhiqiang Guo, Jianjun Li. UGDA: A Unified Graph-based Method with Domain-specific Adaptation for Multi-domain Recommendation. DASFAA 2025. (to appear)

  • Wei Liu, Zhiying Deng, Zhongyu Niu, Jun Wang, Haozhao Wang, Yuankai Zhang, Ruixuan Li. Is the MMI Criterion Necessary for Interpretability? Degenerating Non-causal Features to Plain Noise for Self-Rationalization. NeurIPS 2024. [link]

  • Guohui Li, Li Zou, Zhiying Deng, Qi Chen. Neighborhood-Enhanced Multimodal Collaborative Filtering for Item Cold Start Recommendation. ICASSP 2024. [link]

  • Wei Liu, Haozhao Wang, Jun Wang, Zhiying Deng, Yuankai Zhang, Cheng Wang, Ruixuan Li. Enhancing the Rationale-Input Alignment for Self-explaining Rationalization. ICDE 2024. [link]

  • Zhao Juan, Xiaoquan Yi, Ruixuan Li, Yuhua Li, Haozhao Wang, Yichen Li, Zhiying Deng, Zijun Xu. FedTA: Unsupervised Federated Prototype Learning With Temperature Adaptation. HPCC 2024. (to appear)

  • Wei Liu, Jun Wang, Haozhao Wang, Ruixuan Li, Zhiying Deng, Yuankai Zhang, Yang Qiu. D-Separation for Causal Self-Explanation. NeurIPS 2023. [link]

  • Qian Chen, Jianjun Li, Zhiqiang Guo, Guohui Li, Zhiying Deng. Attribute-enhanced Dual Channel Representation Learning for Session-based Recommendation. CIKM 2023. [link]

  • Juan Zhao, Yuankai Zhang, Ruixuan Li, Yuhua Li, Haozhao Wang, Xiaoquan Yi, Zhiying Deng. XFed: Improving Explainability in Federated Learning by Intersection Over Union Ratio Extended Client Selection. ECAI 2023. [link]