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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, 11 (3), 513-537. 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 |
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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 |
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2026 Journal Article Towards on-device personalization: cloud-device collaborative data augmentation for efficient on-device language modelZhong, Zhaofeng, Yuan, Wei, Qu, Liang, Chen, Tong, Wang, Hao, Zhao, Xiangyu and Yin, Hongzhi (2026). Towards on-device personalization: cloud-device collaborative data augmentation for efficient on-device language model. ACM Transactions on Intelligent Systems and Technology, 17 (1) 3779452, 1-1. doi: 10.1145/3779452 |
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2026 Journal Article Erratum: Lightweight Embeddings with Graph Rewiring for Collaborative FilteringLiang, Xurong, Chen, Tong, Yuan, Wei and Yin, Hongzhi (2026). Erratum: Lightweight Embeddings with Graph Rewiring for Collaborative Filtering. ACM Transactions on Information Systems, 44 (1) C1, 1-1. doi: 10.1145/3785705 |
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2026 Journal Article Scalable and effective negative sample generation for hyperedge predictionQu, Shilin, Wang, Weiqing, Li, Yuan-Fang, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2026). Scalable and effective negative sample generation for hyperedge prediction. Neural Networks, 193 108034, 1-13. doi: 10.1016/j.neunet.2025.108034 |
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2026 Conference Publication Memory-enhanced invariant prompt learning for urban flow prediction under distribution shiftsJiang, Haiyang, Chen, Tong, Zhang, Wentao, Nguyen, Quoc Viet Hung, Yuan, Yuan, Li, Yong and Yin, Hongzhi (2026). Memory-enhanced invariant prompt learning for urban flow prediction under distribution shifts. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2025, Porto, Portugal, 15-19 September 2025. Cham, Switzerland: Springer. doi: 10.1007/978-3-032-06066-2_9 |
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2026 Journal Article ARLIE: Adaptive Reinforcement Learning with Inductive Embeddings for Fully-inductive Multi-hop Reasoning over Temporal Knowledge GraphsZheng, Shangfei, Gao, Yunjun, Liu, An, Li, Wenhao, Chen, Tong and Yin, Hongzhi (2026). ARLIE: Adaptive Reinforcement Learning with Inductive Embeddings for Fully-inductive Multi-hop Reasoning over Temporal Knowledge Graphs. IEEE Transactions on Knowledge and Data Engineering, 38 (5), 1-14. doi: 10.1109/tkde.2026.3666242 |
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2026 Journal Article M2Rec: Multi-scale Mamba for efficient sequential RecommendationZhang, Qianru, Qu, Liang, Wen, Honggang, Huang, Dong, Yiu, Siu-Ming, Hung, Nguyen Quoc Viet and Yin, Hongzhi (2026). M2Rec: Multi-scale Mamba for Efficient Sequential Recommendation. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-14. doi: 10.1109/TKDE.2026.3700323 |
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2026 Journal Article Self-Gating Attention for Efficient Time Series ForecastingWang, Dezheng, Chen, Tong, Yuan, Wei, Chen, Congyan, Li, Shihua and Yin, Hongzhi (2026). Self-Gating Attention for Efficient Time Series Forecasting. IEEE Transactions on Industrial Informatics, PP (99), 1-12. doi: 10.1109/tii.2026.3710167 |
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2026 Journal Article Inductive Message Passing Over Hypergraph for Large-Scale Knowledge Graph CompletionZhang, Yufeng, Chen, Wei, Wang, Weiqing, Yin, Hongzhi and Zhao, Lei (2026). Inductive Message Passing Over Hypergraph for Large-Scale Knowledge Graph Completion. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-15. doi: 10.1109/tkde.2026.3736411 |
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2026 Conference Publication LogicGate: adaptive rule-based modeling of exogenous effects for time series forecastingZhong, Jie, Chen, Tong, Yuan, Wei, Cui, Lizhen and Yin, Hongzhi (2026). LogicGate: Adaptive Rule-Based Modeling of Exogenous Effects for Time Series Forecasting. Lecture Notes in Computer Science. (pp. 239-255) Singapore: Springer Nature Singapore. doi: 10.1007/978-981-92-0375-8_15 |
