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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 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 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 Journal Article H <scp>Mamba</scp> : 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 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 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 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 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, 1-25. 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 Conference Publication On-device large language models for sequential recommendationXia, Xin, Yin, Hongzhi and Culpepper, Shane (2026). On-device large language models for sequential recommendation. WSDM '26: Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, Boise, ID, United States, 22-26 February 2026. New York, NY, United States: ACM. doi: 10.1145/3773966.3777961 |
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2026 Journal Article Generating Compressed Counterfactual Hard Negative Samples for Graph Contrastive LearningYang, Haoran, Chen, Hongxu, Zhao, Xiangyu, Zhang, Sixiao, Sun, Xiangguo, Li, Qian, Yin, Hongzhi and Xu, Guandong (2026). Generating Compressed Counterfactual Hard Negative Samples for Graph Contrastive Learning. CAAI Transactions on Intelligence Technology cit2.70102, 1-14. doi: 10.1049/cit2.70102 |
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2026 Journal Article PPA plus plus : Preference Prototype-Aware Learning with Large Language Model for Universal Cross-Domain RecommendationZhang, Yuxi, Zhang, Ji, Xu, Feiyang, Chen, Lvying, Li, Bohan, Wang, Ning, Tu, Huawei, Guo, Lei and Yin, Hongzhi (2026). PPA plus plus : Preference Prototype-Aware Learning with Large Language Model for Universal Cross-Domain Recommendation. Data Science and Engineering, 11 (1), 213-229. doi: 10.1007/s41019-025-00322-w |
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2026 Journal Article Sparse gradient training for recommender systemsQu, Yunke, Qu, Liang, Chen, Tong, Zhao, Xiangyu, Li, Jianxin and Yin, Hongzhi (2026). Sparse gradient training for recommender systems. Data Science and Engineering, 11 (1), 230-247. doi: 10.1007/s41019-025-00327-5 |
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2026 Journal Article DeepCGC: unveiling the deep clustering mechanism of fast graph condensationGao, Xinyi, Li, Wenjie, Zhao, Xiangyu, Chen, Tong, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2026). DeepCGC: unveiling the deep clustering mechanism of fast graph condensation. IEEE Transactions on Knowledge and Data Engineering, 38 (3), 1575-1588. doi: 10.1109/tkde.2026.3655841 |
