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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 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 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 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 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 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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2025 Conference Publication HGAurban: Heterogeneous Graph Autoencoding for Urban Spatial-Temporal LearningZhang, Qianru, Gao, Xinyi, Wang, Haixin, Huang, Dong, Yiu, Siu-Ming and Yin, Hongzhi (2025). HGAurban: Heterogeneous Graph Autoencoding for Urban Spatial-Temporal Learning. 34th ACM International Conference on Information and Knowledge Management CIKM 2025, Seoul, Korea, 10 - 14 November 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3746252.3761383 |
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2025 Conference Publication Harnessing large language models for Group POI recommendationsLong, Jing, Qu, Liang, Yu, Junliang, Chen, Tong, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2025). Harnessing large language models for Group POI recommendations. 34th ACM International Conference on Information and Knowledge Management CIKM 2025, Seoul, Republic of Korea, 10-14 November 2025. New York, NY, United States: ACM. doi: 10.1145/3746252.3761018 |
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2025 Conference Publication NR-GCF: Graph Collaborative Filtering with Improved Noise ResistanceChen, Yijun, Li, Bohan, Li, Yicong, Song, Lixiang, Wang, Haofen, Wu, Wenlong, Zhuo, Junnan and Yin, Hongzhi (2025). NR-GCF: Graph Collaborative Filtering with Improved Noise Resistance. 34th ACM International Conference on Information and Knowledge Management CIKM 2025, Seoul, Korea, 10 - 14 November 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3746252.3761342 |
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2025 Conference Publication Efficient multimodal streaming recommendation via Expandable Side Mixture-of-ExpertsQu, Yunke, Qu, Liang, Chen, Tong, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2025). Efficient multimodal streaming recommendation via Expandable Side Mixture-of-Experts. CIKM '25: The 34th ACM International Conference on Information and Knowledge Management, Seoul, South Korea, 10-14 November 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3746252.3761390 |
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2025 Conference Publication Multi-task offline reinforcement learning for online advertising in recommender systemsLiu, Langming, Wang, Wanyu, Zhang, Chi, Li, Bo, Yin, Hongzhi, Wei, Xuetao, Su, Wenbo, Zheng, Bo and Zhao, Xiangyu (2025). Multi-task offline reinforcement learning for online advertising in recommender systems. The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Toronto, Canada, 3-7 August 2025. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3711896.3737250 |
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2025 Conference Publication Contrastive graph condensation: advancing data versatility through self-supervised learningGao, Xinyi, Li, Yayong, Chen, Tong, Ye, Guanhua, Zhang, Wentao and Yin, Hongzhi (2025). Contrastive graph condensation: advancing data versatility through self-supervised learning. The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Toronto, Canada, 3-7 August 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3711896.3736892 |
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2025 Conference Publication FindRec: Stein-guided entropic flow for multi-modal sequential recommendationWang, Maolin, Xiao, Yutian, Wang, Binhao, Zhang, Sheng, Ye, Shanshan, Wang, Wanyu, Yin, Hongzhi, Guo, Ruocheng and Xu, Zenglin (2025). FindRec: Stein-guided entropic flow for multi-modal sequential recommendation. The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Toronto, Canada, 3-7 August 2025. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3711896.3736968 |
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2025 Conference Publication Data watermarking for sequential recommender systemsZhang, Sixiao, Long, Cheng, Yuan, Wei, Chen, Hongxu and Yin, Hongzhi (2025). Data watermarking for sequential recommender systems. The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Toronto, Canada, 3-7 August 2025. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3711896.3736903 |
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2025 Conference Publication Progressive Generalization Risk Reduction for Data-Efficient Causal Effect EstimationWen, Hechuan, Chen, Tong, Ye, Guanhua, Chai, Li Kheng, Sadiq, Shazia and Yin, Hongzhi (2025). Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation. KDD '25: The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Toronto, Canada, 3 - 7 August 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3690624.3709305 |
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2025 Conference Publication Diversity-aware dual-promotion poisoning attack on sequential recommendationZhao, Yuchuan, Chen, Tong, Yu, Junliang, Zheng, Kai, Cui, Lizhen and Yin, Hongzhi (2025). Diversity-aware dual-promotion poisoning attack on sequential recommendation. 48th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR 2025), Padua, Italy, 13-18 July 2025. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3726302.3729955 |
