This paper only includes some of the selected publications.
My Google Scholar profile has a more complete list of the publications, and please check it there. :-)
SJR Journal ranking: https://www.scimagojr.com/journalrank.php
CORE conference ranking: http://portal.core.edu.au/conf-ranks/
2025
Jiayang Niu, Yan Wang, Jie Li, Ke Deng, Azadeh Alavi, Mark Sanderson, Yongli Ren. Hybrid action Reinforcement Learning for quantum architecture search. 2025. https://arxiv.org/abs/2511.04967
Sishun Liu, Ke Deng, Xiuzhen Zhang, Yongli Ren, Yan Wang. Addressing Mark Imbalance using Integration-free Marked Temporal Point Processes. NeurIPS 2025 (CORE A*)
Azadeh Alavi, Fatemeh Kouchmeshki, Abdolrahman Alavi, Yongli Ren, Jiayang Niu. Quantum Semi-Random Forests for Qubit-Efficient Recommender Systems. 2025 IEEE International Conference on Quantum Artificial Intelligence. 2025.
Bo Zhao, Yinghao Zhang, Ziqi Xu, Yongli Ren, Xiuzhen Zhang, Renqiang Luo, Zaiwen Feng and Feng Xia. Unbiased Reasoning for Knowledge-Intensive Tasks in Large Language Models via Conditional Front-Door Adjustment. CIKM 2025 (CORE Rank A)
Jiayang Niu, Qihan Zou, Jie Li, Ke Deng, Mark Sanderson and Yongli Ren. Estimating Quantum Execution Requirements for Feature Selection in Recommender Systems Using Extreme Value Theory. RecSys 2025. (CORE A)
Chenglong Ma, Ziqi Xu, Yongli Ren, Danula Hettiachchi, Jeffrey Chan. PUB: An LLM-Enhanced Personality-Driven User Behaviour Simulator for Recommender System Evaluation. SIGIR 2025.
Ziqi Xu, Chenglong Ma, Yongli Ren, Jeffrey Chan, Wei Shao and Feng Xia. Towards Better Evaluation of Recommendation Algorithms with Bi-directional Item Response Theory. WWW 2025.
Tony Danhui Huang, Yongli Ren and Xiuzhen Zhang. Can Large Language Models Be a Good Evaluator for Review-based Product Question Answering? WWW 2025.
Jie Li, Ke Deng, Jianxin Li, Yongli Ren: Session-Oriented Fairness-Aware Recommendation via Dual Temporal Convolutional Networks. IEEE Trans. Knowl. Data Eng. 37(2): 923-935 (2025)
Futoon M. Abushaqra, Hao Xue, Yongli Ren, Flora D. Salim: ODEStream: A Buffer-Free Online Learning Framework with ODE-based Adaptor for Streaming Time Series Forecasting. Trans. Mach. Learn. Res. 2025 (2025)
Jie Li, Yongli Ren, Mark Sanderson, Ke Deng: Explaining Recommendation Fairness from a User/Item Perspective. ACM Trans. Inf. Syst. 43(1): 17:1-17:30 (2025)