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2026 Journal Article Efficient prompt learning for traffic forecastingZhang, Qianru, Gao, Xinyi, Zhou, Alexander, Cheng, Reynold, Yiu, Siu-Ming and Yin, Hongzhi (2026). Efficient prompt learning for traffic forecasting. VLDB Journal, 35 (5) 45. doi: 10.1007/s00778-026-00983-7 |
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2026 Conference Publication Learning to Evaluate: Cost-Effective Model Evaluation on Unlabeled Data with Meta-LearningPham, Trinh, Huynh, Viet, Yin, Hongzhi, Nguyen, Quoc Viet Hung and Nguyen, Thanh Tam (2026). Learning to Evaluate: Cost-Effective Model Evaluation on Unlabeled Data with Meta-Learning. New York, NY, USA: ACM. doi: 10.1145/3770855.3818104 |
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2026 Conference Publication LEFT: Learnable Fusion of Tri-view Tokens for Unsupervised Time Series Anomaly DetectionWang, Dezheng, Chen, Tong, Pang, Guansong, Chen, Congyan, Li, Shihua and Yin, Hongzhi (2026). LEFT: Learnable Fusion of Tri-view Tokens for Unsupervised Time Series Anomaly Detection. New York, NY, USA: ACM. doi: 10.1145/3770855.3818044 |
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2026 Conference Publication Prompt-Unknown Promotion Attacks against LLM-based Sequential Recommender SystemsZhao, Yuchuan, Chen, Tong, Yu, Junliang, Wang, Zongwei, Cui, Lizhen and Yin, Hongzhi (2026). Prompt-Unknown Promotion Attacks against LLM-based Sequential Recommender Systems. New York, NY, USA: ACM. doi: 10.1145/3805712.3809691 |
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2026 Conference Publication ProEchoMem: Enhancing Long Video Understanding via Multi-Trace Probe-Echo MemoryXu, Derong, Chen, Yanxin, Wang, Wanyu, Jia, Pengyue, Zhang, Chao, Wang, Maolin, Wang, Yiqi, Qiang, Jipeng, Wei, Xuetao, Yin, Hongzhi, Xu, Tong and Zhao, Xiangyu (2026). ProEchoMem: Enhancing Long Video Understanding via Multi-Trace Probe-Echo Memory. New York, NY, USA: ACM. doi: 10.1145/3805712.3809599 |
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2026 Conference Publication ProMax: Exploring the Potential of LLM-derived Profiles with Distribution Shaping for Recommender SystemsZhang, Yi, Zhang, Yiwen, Zheng, Kai, Chen, Tong and Yin, Hongzhi (2026). ProMax: Exploring the Potential of LLM-derived Profiles with Distribution Shaping for Recommender Systems. New York, NY, USA: ACM. doi: 10.1145/3805712.3809600 |
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2026 Conference Publication LLM-UP: SIGIR 2026 Workshop on LLM-powered User Profiling for Search and RecommendationYin, Hongzhi, Yuan, Wei, Zhang, Yi, Mackenzie, Joel, Nguyen, Quoc Viet Hung, Zhao, Wayne Xin, Li, Yong and Yao, Lina (2026). LLM-UP: SIGIR 2026 Workshop on LLM-powered User Profiling for Search and Recommendation. New York, NY, USA: ACM. doi: 10.1145/3805712.3808652 |
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2026 Journal Article Multi-agents Based User Values Mining for RecommendationChen, Lijian, Yuan, Wei, Chen, Tong, Zhao, Xiangyu, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2026). Multi-agents Based User Values Mining for Recommendation. Data Science and Engineering, 1-20. doi: 10.1007/s41019-026-00349-7 |
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2026 Journal Article H Mamba: hyperbolic mamba for sequential recommendationZhang, Qianru, Wen, Honggang, Yuan, Wei, Chen, Crystal, Yang, Menglin, Yiu, Siu-Ming and Yin, Hongzhi (2026). H Mamba: hyperbolic mamba for sequential recommendation. ACM Transactions on Information Systems, 44 (5) 3811405, 1-27. doi: 10.1145/3811405 |
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2026 Journal Article Cassette: Case-to-Case Structural Distillation for Efficient Legal Case RetrievalTang, Yanran, Qiu, Ruihong, Yin, Hongzhi, Li, Xue and Huang, Zi (2026). Cassette: Case-to-Case Structural Distillation for Efficient Legal Case Retrieval. ACM Transactions on Information Systems, 44 (5) 3816732, 1-27. doi: 10.1145/3816732 |
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2026 Journal Article A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model EraLi, Zongru, Chen, Xingsheng, Wen, Honggang, Zhang, Regina Qianru, Li, Ming, Zhang, Xiaojin, Yin, Hongzhi, Yang, Qiang, Lam, Kwok-Yan, Lio, Pietro and Yiu, Siu-Ming (2026). A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era. Journal of Chemical Theory and Computation, 22 (10) acs.jctc.5c02081, 4866-4887. doi: 10.1021/acs.jctc.5c02081 |
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2026 Conference Publication ProEx: a unified framework leveraging large language model with profile extrapolation for recommendationZhang, Yi, Zhang, Yiwen, Wang, Yu, Chen, Tong and Yin, Hongzhi (2026). ProEx: a unified framework leveraging large language model with profile extrapolation for recommendation. KDD '26: Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Jeju, Korea, 9 - 13 August 2026. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3770854.3780284 |
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2026 Conference Publication Relational Database Distillation: From Structured Tables to Condensed Graph DataGao, Xinyi, Zhang, Jingxi, Chen, Lijian, Chen, Tong, Cui, Lizhen and Yin, Hongzhi (2026). Relational Database Distillation: From Structured Tables to Condensed Graph Data. New York, NY, USA: ACM. doi: 10.1145/3774904.3792734 |
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2026 Conference Publication Efficient content-based recommendation model training via noise-aware coreset selectionTran, Hung Vinh, Chen, Tong, Wen, Hechuan, Nguyen, Quoc Viet Hung, Cui, Bin and Yin, Hongzhi (2026). Efficient content-based recommendation model training via noise-aware coreset selection. WWW '26: Proceedings of the ACM Web Conference 2026, Dubai United Arab Emirates, 13 - 17 April 2026. New York, NY, United States: Association for Computing Machinery, Inc. doi: 10.1145/3774904.3792686 |
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2026 Journal Article Tackling data heterogeneity in federated time series forecastingYuan, Wei, Yang, Chaoqun, Zhao, Xiangyu, Nguyen, Quoc Viet Hung, Cao, Yang, He, Tieke and Yin, Hongzhi (2026). Tackling data heterogeneity in federated time series forecasting. Science China-Information Sciences, 69 (5) 152102. doi: 10.1007/s11432-025-4553-x |
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2026 Journal Article Handling data sparsity and model poisoning attacks in federated sequential recommender systemsNguyen, Minh Hieu, Nguyen, Thanh Tam, Jo, Jun, Nguyen, Duc Anh, Yin, Hongzhi and Nguyen, Quoc Viet Hung (2026). Handling data sparsity and model poisoning attacks in federated sequential recommender systems. Knowledge-Based Systems, 338 115545, 1-12. doi: 10.1016/j.knosys.2026.115545 |
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2026 Journal Article A survey of generative techniques for spatial-temporal data miningZhang, Qianru, Wang, Haixin, Wen, Honggang, Long, Cheng, Su, Liangcai, He, Xingwei, Wu, Tailin, Jensen, Christian S., Yiu, Siu-Ming and Yin, Hongzhi (2026). A survey of generative techniques for spatial-temporal data mining. Data Science and Engineering. doi: 10.1007/s41019-026-00346-w |
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2026 Conference Publication SmartAgent: chain-of-user-thought for embodied personalized agent in cyber worldZhang, Jiaqi, Gao, Chen, Zhang, Liyuan, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2026). SmartAgent: chain-of-user-thought for embodied personalized agent in cyber world. Fortieth AAAI Conference on Artificial Intelligence, Singapore, Singapore, 20 - 27 January 2026. Washington, DC, United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v40i21.38859 |
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2026 Journal Article A comprehensive survey on imbalanced data learningGao, Xinyi, Xie, Dongting, Zhang, Yihang, Wang, Zhengren, Chen, Chong, He, Conghui, Yin, Hongzhi and Zhang, Wentao (2026). A comprehensive survey on imbalanced data learning. Frontiers of Computer Science, 20 (11) 2011622. doi: 10.1007/s11704-025-50274-7 |
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2026 Journal Article A survey on sequential recommendationPan, Li-Wei, Pan, Wei-Ke, Wei, Mei-Yan, Yin, Hong-Zhi and Ming, Zhong (2026). A survey on sequential recommendation. Frontiers of Computer Science, 20 (3) 2003606. doi: 10.1007/s11704-025-41329-w |
