Yue Cui

Publications

• Yue Cui, Liuyi Yao, Shuchang Tao, Weijie Shi, Yaliang Li, Bolin Ding, Xiaofang Zhou. Enhancing Tool Learning in Large Language Models with Hierarchical Error Checklists. ACL (CCF A, CORE A*) Finding, 2025.

• Yue Cui, Liuyi Yao, Zitao Li, Yaliang Li, Bolin Ding, and Xiaofang Zhou. Efficient Leave-one-out Approximation in LLM Multi-agent Debate Based on Introspection. arXiv 2505.22192, 2025, preprint.

• Yue Cui, Liuyi Yao, Yaliang Li, Ziqian Chen, Jinyang Gao, Bolin Ding, and Xiaofang Zhou. A Marketplace for Federated Learning: An Auction-based Solution. arXiv 2402.01802, 2024, preprint.

• Yue Cui, Liuyi Yao, Zitao Li, Yaliang Li, Jinyang Gao, Bolin Ding, and Xiaofang Zhou. A Bargaining-based Approach for Feature Trading in Vertical Federated Learning. ICDE (CCF A, CORE A*), 2025, pp. 1001-1014.

• Yue Cui, Chung-ju Huang, Yuzhu Zhang, Leye Wang, Lixin Fan, Xiaofang Zhou, and Qiang Yang. A Survey on Contribution Evaluation in Vertical Federated Learning. arXiv 2405.02364, 2024, preprint.

• Weiyang Guo*, Yue Cui``, and Kai Zheng. IntFair: Graph Neural Networks for Fair Recommendations with Interest Awareness. DASFAA (CCF B, CORE B), 2024.

• Xuanran Yu*, Yue Cui``, and Kai Zheng. An Efficient SVM-based Method for Client Access Permission Distribution in Federated Learning. DASFAA (CCF B, CORE B), 2024.

• Yue Cui, Chen Ma, Kai Zheng, Lei Chen, and Xiaofang Zhou. Universal Fair Representation Learning. WWW (CCF A, CORE A*), 2023, pp. 949-959.

• Yue Cui, Shuhao Li, Wenjin Deng, Zhaokun Zhang, Jing Zhao, Kai Zheng, and Xiaofang Zhou. ROI-demand Traffic Prediction: A Pre-train, Query and Fine-tune Framework. ICDE (CCF A, CORE A*), 2023, pp. 1340-1352.

• Yue Cui, Kai Zheng, Dingshan Cui, Jiandong Xie, Liwei Deng, Feiteng Huang, and Xiaofang Zhou. METRO: A Generic Graph Neural Network Framework for Multivariate Time Series Forecasting. PVLDB (CCF A, CORE A*), 2022, pp. 224-236.

• Yue Cui, Hao Sun, Yan Zhao, Hongzhi Yin, and Kai Zheng. Sequential-knowledge-aware POI Recommendation: A Meta-learning Approach. ACM Transactions on Information Systems (CCF A, CORE A*), 2022, pp. 1-22.

• Yue Cui, Liwei Deng, Yan Zhao, Vincent Zheng, Bin Yao, and Kai Zheng. Hidden POI Ranking with Spatial Crowdsourcing. KDD (CCF A, CORE A*), 2019, pp. 814-824.

• Yue Cui, Chen Zhu, Guanyu Ye, Ziwei Wang, and Kai Zheng. Into the Unobservables: A Multi-range Encoder-decoder Framework for COVID-19 Prediction. CIKM (CCF B, CORE A), 2021, pp. 292–301.

• Yue Cui, Jiandong Xie, and Kai Zheng. Historical Inertia: An Ignored But Powerful Baseline for Long Sequence Time-series Forecasting. CIKM (CCF B, CORE A), 2021, pp. 2965–2969.

• Shuhao Li*,, Yue Cui, Jingyi Xu, Libin Li, Lingkai Meng, Weidong Yang, Fan Zhang, Xiaofang Zhou. Unifying Lane-Level Traffic Prediction from a Graph Structural Perspective: Benchmark and Baseline. TKDE (CCF A, CORE A*), 2025.

• Shuhao Li*, Yue Cui, Libin Li, Weidong Yang, Fan Zhang, and Xiaofang Zhou. ST-ABC: Spatio-Temporal Attention-Based Convolutional Network for Multi-Scale Lane-Level Trac Prediction. ICDE (CCF A, CORE A*), 2024.

• Kai Huang, Yue Cui, Qingqing Ye, Yan Zhao, Xi Zhao, Yao Tian, Kai Zheng, Haibo Hu, and Xiaofang Zhou. TED+: Towards Discovering Top-k Edge-Diversified Patterns in a Graph Database. TKDE (CCF A, CORE A*), 2023.

• Shuhao Li*^,  Yue Cui^, Yan Zhao, Ruiyuan Zhang, Weidong Yang, and Xiaofang Zhou. ST-MoE: Spatio-Temporal Mixture-of-Experts for Debiasing in Traffic Prediction. CIKM (CCF B, CORE A), 2023, pp. 1208-1217.

• Chen Zhu*, Yue Cui, Yan Zhao, and Kai Zheng. Task Assignment with Spatio-temporal Recommendation in Spatial Crowdsourcing. APWeb-WAIM, 2022, Best Paper Award Runner Up.

• Jiandong Xie, Yue Cui, Feiteng Huang, Chao Liu, and Kai Zheng. MARINA: A Unied MLP-Attention Model for Multivariate Time-Series Analysis. CIKM (CCF B, CORE A), 2022, pp. 2230-2239.

• Bingke Xu*^, Yue Cui^, Zipeng Sun, Liwei Deng, and Kai Zheng. Fair Representation Learning in Knowledge-aware Recommendation. ICBK, 2021, pp. 385-392.

• Samuel Gagnon-Hartman, Yue Cui, Adrian Liu, and Siamak Ravanbakhsh. Recovering the Lost Wedge Modes in 21-cm Foregrounds. Monthly Notices of the Royal Astronomical Society (IF 8.938), 2021, pp. 4716–4729.

• Shuhao Li*, Weidong Yang, Yue Cui, Xiaoxing Liu, Lingkai Meng, Lipeng Ma, Fan Zhang. Fine-Grained Traffic Inference from Road to Lane via Spatio-Temporal Graph Node Generation. KDD (CCF A, CORE A*), 2025.

• Liwei Deng, Yan Zhao, Yue Cui, Yuyang Xiao, Jin Chen, and Kai Zheng. Task Recommendation in Spatial Crowdsourcing: A Trade-off between Diversity and Coverage. ICDE (CCF A, CORE A*), 2024.

• Banghua Wu, Linjie Li*, Yue Cui, and Kai Zheng. Cross Adversarial Learning for Molecular Generation in Drug Design. Frontiers in Pharmacology (IF 5.988), 2022, pp. 4716–4729.

• Hao Sun, Zijian Wu, Yue Cui, Liwei Deng, Defu Lian, and Kai Zheng. Personalized Dynamic Knowledge-aware Recommendation with Hybrid Explanations. DASFAA (CCF B, CORE B), 2021, pp. 148-164.

• Yan Zhao, Kai Zheng, Yue Cui, Han Su, Feida Zhu, and Xiaofang Zhou. Predictive Task Assignment in Spatial Crowdsourcing: A Data-driven Approach. ICDE (CCF A, CORE A*), 2020, pp. 13-24.

• Yuchen Fang, Hao Miao, Yuxuan Liang, Liwei Deng, Yue Cui, Ximu Zeng, Yuyang Xia, Yan Zhao, Torben Bach Pedersen, Christian S. Jensen, Xiaofang Zhou, Kai Zheng. Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review. arxiv 2506.01364. 2025, preprint.

• Kai Huang, Yunqi Li, Qingqing Ye, Yao Tian, Xi Zhao, Yue Cui, Haibo Hu, and Xiaofang Zhou. FRESH: Towards Efficient Graph Queries in an Outsourced Graph. ICDE (CCF A, CORE A*), 2024.

• Kai Huang, Houdong Liang, Chongchong Yao, Xi Zhao, Yue Cui, Yao Tian, Ruiyuan Zhang,  and Xiaofang Zhou. VisualNeo: Bridging the Gap between Visual Query Interfaces and Graph Query Engines. PVLDB (CCF A, CORE A*) Demo, 2023.

• Hanghui Guo, Weijie Shi, Mengze Li, Juncheng Li, Hao Chen, Yue Cui, Jiajie Xu, Jia Zhu, Jiawei Shen, Zhangze Chen, and Sirui Han. Consistent and Invariant Generalization Learning for Short-video Misinformation Detection. ACM MM  (CCF A, CORE A*), 2025

• Jacob Kennedy, Jonathan Colaco Carr, Samuel Gagnon-Hartman, Adrian Liu, Jordan Mirocha, and Yue Cui. Machine-learning recovery of foreground wedge-removed 21-cm light cones for high-z galaxy mapping. Monthly Notices of the Royal Astronomical Society (IF 8.938), 2023.

*Mentored student

^Euqal contribution

``Corresponding author

Selected Honors and Awards

• Redbird Scholarship, HKUST, 2021-22, 2022-23

• Outstanding Graduate of Sichuan Province, 2020

• Outstanding Undergraduate Thesis Award of UESTC, 2020

• KDD 2019 Student Travel Award, 2019

• Chinese Government Scholarship, 2019

• SenseTime Scholarship (29 winners around China), 2019

• Globalink Research Internship Award of Mitacs, Canada, 2019

• HUAWEI Scholarship, 2019

• National Scholarship of China (top 0.4%), 2018

• National Scholarship of Encouragement of China, 2019, 2017

• 1st-class Scholarship of UESTC, 2019, 2018, 2017

• Outstanding Student Scholarship of School of Computer Science & Engineering, 2019, 2018

• 1st prize in Undergraduate Physics Tournament of China, South-West Division, 2017

• 1st prize in College Mathematical Competition of UESTC (Top 1%), 2018

Professional Services and Teaching

PC Member/Reviewer:

•  Conferences: MM(2025), SDM (2024), DASFAA (2023, 2024), KDD (2023, 2025), ICDE (2023), BDMS@DASFAA (2023), SDM (2023), ICML (2022), CIKM (2021)

• Journals: IEEE/ACM Transactions on Networking (2024 - now), Springer Nature Computer Science (2020 - now)

Workshop co-organizer: 

• DMF@ICDM (2025, 2024,  2023) call for paper

Teaching:

• COMP 1021 TA (2023), COMP 3311 TA (2022)