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ORCIDPhilip S. Yu
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- affiliation: University of Illinois at Chicago, Department of Computer Science, Chicago, IL, USA
- affiliation (PhD): Stanford University, Stanford, CA, USA
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2020 – today
- 2026
[j685]Yuqing Liang, Jiancheng Xiao, Wensheng Gan, Philip S. Yu:
Watermarking techniques for large language models: a survey. Artif. Intell. Rev. 59(2): 74 (2026)- [j684]Lingzhe Zhang
, Tong Jia, Mengxi Jia, Yifan Wu, Aiwei Liu, Yong Yang, Zhonghai Wu, Xuming Hu, Philip S. Yu, Ying Li:
A Survey of AIOps in the Era of Large Language Models. ACM Comput. Surv. 58(2): 44:1-44:35 (2026) - [j683]Shang Wang, Tianqing Zhu, Bo Liu, Ming Ding, Dayong Ye, Wanlei Zhou, Philip S. Yu:
Unique Security and Privacy Threats of Large Language Models: A Comprehensive Survey. ACM Comput. Surv. 58(4): 83:1-83:36 (2026) - [j682]Feng He, Tianqing Zhu, Dayong Ye, Bo Liu, Wanlei Zhou, Philip S. Yu:
The Emerged Security and Privacy of LLM Agent: A Survey with Case Studies. ACM Comput. Surv. 58(6): 162:1-162:36 (2026) - [j681]Panpan Meng, Chenxu Wang, Shihao Wang, Kay Liu, Yankai Chen, Zhanggong Wang, Philip S. Yu:
Community-aware multi-granularity contrastive learning for graph anomaly detection. Expert Syst. Appl. 305: 130872 (2026) - [j680]Libo Qin, Qiguang Chen, Xiachong Feng, Yang Wu, Yongheng Zhang, Yinghui Li, Min Li, Wanxiang Che, Philip S. Yu:
Large language models meet NLP: a survey. Frontiers Comput. Sci. 20(11): 2011361 (2026) - [j679]Li Sun, Philip S. Yu:
A Riemannian perspective on graph foundation models: curvature as a guiding principle. Frontiers Comput. Sci. 20(12): 2012370 (2026) - [j678]Wensheng Gan, Zhenyao Ning, Zhenlian Qi, Philip S. Yu:
Mixture of experts (MoE): A big data perspective. Inf. Fusion 127: 103664 (2026) - [j677]Jibing Gong, Jiquan Peng, Wei Wang, Wei Zhou, Chaozhuo Li, Philip S. Yu:
Beyond embedding-mapping: Social network alignment via generative information fusion and LLM-guided iterative mechanism. Inf. Fusion 127: 103733 (2026) - [j676]Mingying Xu, Fei Hou, Jie Liu, Mengmei Zhang, Lei Shi, Feifei Kou, Lei Guo, Philip S. Yu, Xuming Hu:
Multimodal named entity recognition in the era of large pre-trained models: A comprehensive survey. Inf. Fusion 127: 103767 (2026) - [j675]Qingfeng Zhou, Wensheng Gan, Zhenlian Qi, Philip S. Yu:
Utility-Based Privacy-Preserving Data Mining. IEEE Internet Things J. 13(2): 2067-2084 (2026) - [j674]Yiting Huang, Yu-Ming Shang, Wei Huang, Sanchuan Guo, Jinhu Chen, Xi Zhang, Philip S. Yu:
Discovering new intents via spatio-temporal pseudo-label denoising. Inf. Process. Manag. 63(2): 104381 (2026) - [j673]Zeyu Zhang, Lu Li, Xingyu Ji, Kaiqi Zhao, Xiaofeng Zhu, Philip S. Yu, Jiawei Li, Maojun Wang:
Enhancing signed graph neural networks through curriculum-based training. Neural Networks 193: 107975 (2026) - [j672]Bo Yu, Jiuman Song, Lele Cong, Xianling Cong, Jouke Dijkstra, Philip S. Yu, Hechang Chen:
A prompt-aware knowledge-tuning framework for histopathology subtype classification with scarce annotation. Neural Networks 193: 107993 (2026) - [j671]Ling Huang, Zhe-Yuan Li, Xiao-Dong Huang, Yuefang Gao, Chang-Dong Wang, Philip S. Yu:
Autoencoder-based contrastive learning for next basket recommendation. Neural Networks 194: 108166 (2026) - [j670]Fanlong Zeng, Wensheng Gan, Jiayang Wu, Philip S. Yu:
Pure node selection for imbalanced graph node classification. Neural Networks 196: 108315 (2026) - [j669]Yi Wang, Zhenghong Wang, Fan Zhang, Chaogui Kang, Sijie Ruan, Di Zhu, Chengling Tang, Zhongfu Ma, Weiyu Zhang, Yu Zheng, Philip S. Yu, Yu Liu:
A Gravity-Informed Spatiotemporal Transformer for Human Activity Intensity Prediction. IEEE Trans. Pattern Anal. Mach. Intell. 48(3): 2380-2397 (2026) - [j668]Qingyun Sun, Jiayi Luo, Haonan Yuan, Xingcheng Fu, Hao Peng, Jianxin Li, Philip S. Yu:
Evolving Graph Learning for Out-of-Distribution Generalization in Non-Stationary Environments. IEEE Trans. Pattern Anal. Mach. Intell. 48(3): 2714-2730 (2026) - [j667]Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Philip S. Yu, Ming Zhang:
A Survey of Graph Neural Networks in Real World: Imbalance, Noise, Privacy and OOD Challenges. IEEE Trans. Pattern Anal. Mach. Intell. 48(3): 3036-3055 (2026) - [j666]Lixiang Xu, Xianwei Ding, Xin Yuan, Zhanlong Wang, Lu Bai, Enhong Chen, Philip S. Yu, Yuanyan Tang:
Improving Question Embeddings With Cognitive Representation Optimization for Knowledge Tracing. IEEE Trans. Cybern. 56(1): 235-248 (2026) - [j665]Junyou Zhu, Christian Nauck, Michael Lindner, Langzhou He, Philip S. Yu, Klaus-Robert Müller, Jürgen Kurths, Frank Hellmann:
Network Measure-Enriched GNNs: A New Framework for Power Grid Stability Prediction. IEEE Trans. Knowl. Data Eng. 38(1): 518-531 (2026) - [j664]Qihua Feng, Chunhui Duan, Jiawei Xue, Chaozhuo Li, Feiran Huang, Xi Zhang, Jian Weng, Philip S. Yu:
Imbalanced Semi-Supervised Learning for WiFi Gesture Recognition via Dynamic Threshold-Based Spatio-Temporal Attention Networks. IEEE Trans. Mob. Comput. 25(1): 483-499 (2026) - [j663]Shuang Liang, Lili Chen, Wensheng Gan, Philip S. Yu, Shengjie Zhao:
Targeted Mining of Time-Interval Related Patterns. IEEE Trans. Neural Networks Learn. Syst. 37(2): 937-950 (2026) - [j662]Jianguo Chen, Zeju Cai, Wenqing Chen, Weicheng Wang, Zibin Zheng, Philip S. Yu:
A Federated Adaptive Large Language Model Fine-Tuning Framework for Software Development. IEEE Trans. Serv. Comput. 19(1): 32-43 (2026) - [j661]Man-Sheng Chen, Li-An Ren, Wu-Dong Xi, Chang-Dong Wang, Philip S. Yu:
Knowledge-Aware Clustering. IEEE Trans. Syst. Man Cybern. Syst. 56(2): 1165-1178 (2026) - [c1179]Guangjie Zeng, Hao Peng, Angsheng Li, Li Sun, Chunyang Liu, Shengze Li, Yicheng Pan, Philip S. Yu:
Hyperbolic Continuous Structural Entropy for Hierarchical Clustering. AAAI 2026: 28094-28102 - [e40]Feida Zhu, Philip S. Yu, Akiyo Nadamoto, Ee-Peng Lim, Kyuseok Shim, Wei Ding, Bingxue Zhang:
Database Systems for Advanced Applications - 30th International Conference, DASFAA 2025, Singapore, Singapore, May 26-29, 2025, Proceedings, Part II. Lecture Notes in Computer Science 15987, Springer 2026, ISBN 978-981-95-3829-4 [contents] - [e39]Feida Zhu, Philip S. Yu, Akiyo Nadamoto, Ee-Peng Lim, Kyuseok Shim, Wei Ding, Bingxue Zhang:
Database Systems for Advanced Applications - 30th International Conference, DASFAA 2025, Singapore, Singapore, May 26-29, 2025, Proceedings, Part III. Lecture Notes in Computer Science 15988, Springer 2026, ISBN 978-981-95-3905-5 [contents] - [e38]Feida Zhu, Philip S. Yu, Akiyo Nadamoto, Ee-peng Lim, Kyuseok Shim, Wei Ding, Bingxue Zhang:
Database Systems for Advanced Applications - 30th International Conference, DASFAA 2025, Singapore, Singapore, May 26-29, 2025, Proceedings, Part V. Lecture Notes in Computer Science 15990, Springer 2026, ISBN 978-981-95-4154-6 [contents] - [e37]Feida Zhu, Philip S. Yu, Akiyo Nadamoto, Ee-Peng Lim, Kyuseok Shim, Wei Ding, Bingxue Zhang:
Database Systems for Advanced Applications - 30th International Conference, DASFAA 2025, Singapore, Singapore, May 26-29, 2025, Proceedings, Part VI. Lecture Notes in Computer Science 15991, Springer 2026, ISBN 978-981-95-4157-7 [contents] - [i658]Lili Chen, Wensheng Gan, Shuang Liang, Philip S. Yu:
Enhancing Temporal Awareness in LLMs for Temporal Point Processes. CoRR abs/2601.00845 (2026) - [i657]Yujie Feng, Hao Wang, Jian Li, Xu Chu, Zhaolu Kang, Yiran Liu, Yasha Wang, Philip S. Yu, Xiao-Ming Wu:
FOREVER: Forgetting Curve-Inspired Memory Replay for Language Model Continual Learning. CoRR abs/2601.03938 (2026) - [i656]Qitong Liu, Hao Peng, Zuchen Li, Xihang Meng, Ziyu Yang, Jiting Li, Li Sun, Philip S. Yu:
Effective and Unsupervised Social Event Detection and Evolution via RAG and Structural Entropy. CoRR abs/2601.12035 (2026) - [i655]Daixian Liu, Jiayi Kuang, Yinghui Li, Yangning Li, Di Yin, Haoyu Cao, Xing Sun, Ying Shen, Hai-Tao Zheng, Liang Lin, Philip S. Yu:
TangramPuzzle: Evaluating Multimodal Large Language Models with Compositional Spatial Reasoning. CoRR abs/2601.16520 (2026) - [i654]Yusheng Zhao, Jiaye Xie, Qixin Zhang, Weizhi Zhang, Xiao Luo, Zhiping Xiao, Philip S. Yu, Ming Zhang:
DREAM: Dual-Standard Semantic Homogeneity with Dynamic Optimization for Graph Learning with Label Noise. CoRR abs/2601.17449 (2026) - [i653]Zhixiao Wang, Chaofan Zhu, Qihan Feng, Jian Zhang, Xiaobin Rui, Philip S. Yu:
GraphSB: Boosting Imbalanced Node Classification on Graphs through Structural Balance. CoRR abs/2601.19352 (2026) - [i652]Jiahao Huo, Yu Huang, Yibo Yan, Ye Pan, Yi Cao, Mingdong Ou, Philip S. Yu, Xuming Hu:
CausalEmbed: Auto-Regressive Multi-Vector Generation in Latent Space for Visual Document Embedding. CoRR abs/2601.21262 (2026) - [i651]Zhenqiang Ye, Wensheng Gan, Gengsen Huang, Tianlong Gu, Philip S. Yu:
Discovering High-utility Sequential Rules with Increasing Utility Ratio. CoRR abs/2601.22178 (2026) - [i650]Chunkai Zhang, Jiarui Deng, Maohua Lyu, Wensheng Gan, Philip S. Yu:
High-utility Sequential Rule Mining Utilizing Segmentation Guided by Confidence. CoRR abs/2601.22179 (2026) - [i649]Jie Yang, Yifan Hu, Yuante Li, Kexin Zhang, Kaize Ding, Philip S. Yu:
From Observations to States: Latent Time Series Forecasting. CoRR abs/2602.00297 (2026) - [i648]Pengyu Zhu, Li Sun, Philip S. Yu, Sen Su:
The Necessity of a Unified Framework for LLM-Based Agent Evaluation. CoRR abs/2602.03238 (2026) - [i647]Wei-Chieh Huang, Weizhi Zhang, Yueqing Liang, Yuanchen Bei, Yankai Chen, Tao Feng, Xinyu Pan, Zhen Tan, Yu Wang, Tianxin Wei, Shanglin Wu, Ruiyao Xu, Liangwei Yang, Rui Yang, Wooseong Yang, Chin-Yuan Yeh, Hanrong Zhang, Haozhen Zhang, Siqi Zhu, Henry Peng Zou, Wanjia Zhao, Song Wang, Wujiang Xu, Zixuan Ke, Zheng Hui, Dawei Li, Yaozu Wu, Langzhou He, Chen Wang, Xiongxiao Xu, Baixiang Huang, Juntao Tan, Shelby Heinecke, Huan Wang, Caiming Xiong, Ahmed A. Metwally, Jun Yan, Chen-Yu Lee, Hanqing Zeng, Yinglong Xia, Xiaokai Wei, Ali Payani, Yu Wang, Haitong Ma, Wenya Wang, Chenguang Wang, Yu Zhang, Xin Wang, Yongfeng Zhang, Jiaxuan You, Hanghang Tong, Xiao Luo, Xue Liu, Yizhou Sun, Wei Wang, Julian J. McAuley, James Zou, Jiawei Han, Philip S. Yu, Kai Shu:
Rethinking Memory Mechanisms of Foundation Agents in the Second Half: A Survey. CoRR abs/2602.06052 (2026) - [i646]Qianren Mao, Yashuo Luo, Ziqi Qin, Junnan Liu, Weifeng Jiang, Zhijun Chen, Zhuoran Li, Likang Xiao, Chuou Xu, Qili Zhang, Hanwen Hao, Jingzheng Li, Chunghua Lin, Jianxin Li, Philip S. Yu:
NanoNet: Parameter-Efficient Learning with Label-Scarce Supervision for Lightweight Text Mining Model. CoRR abs/2602.06093 (2026) - 2025
- [j660]Zhilin Zhao, Longbing Cao, Philip S. Yu:
Out-of-distribution detection by regaining lost clues. Artif. Intell. 339: 104275 (2025) - [j659]Yue Xing, Wensheng Gan, Qidi Chen, Philip S. Yu:
AI-generated content in landscape architecture: A survey. AI Open 6: 220-243 (2025) - [j658]Haishuai Wang, Yang Gao, Xin Zheng, Peng Zhang, Jiajun Bu, Philip S. Yu:
Graph neural architecture search with large language models. Sci. China Inf. Sci. 68(12) (2025) - [j657]Aiwei Liu, Leyi Pan, Yijian Lu, Jingjing Li, Xuming Hu, Xi Zhang, Lijie Wen, Irwin King, Hui Xiong, Philip S. Yu:
A Survey of Text Watermarking in the Era of Large Language Models. ACM Comput. Surv. 57(2): 47:1-47:36 (2025) - [j656]Yihan Cao, Siyu Li, Yixin Liu, Zhiling Yan, Yutong Dai, Philip S. Yu, Lichao Sun:
A Survey of AI-Generated Content (AIGC). ACM Comput. Surv. 57(5): 125:1-125:38 (2025) - [j655]Haopeng Zhang, Philip S. Yu, Jiawei Zhang:
A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models. ACM Comput. Surv. 57(11): 277:1-277:41 (2025) - [j654]Xi Zhu, Yu Wang, Hang Gao, Wujiang Xu, Chen Wang, Zhiwei Liu, Kun Wang, Mingyu Jin, Linsey Pang, Qingsong Weng, Philip S. Yu, Yongfeng Zhang:
Recommender Systems Meet Large Language Model Agents: A Survey. Found. Trends Priv. Secur. 7(4): 247-396 (2025) - [j653]Laiqiao Qin, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Knowledge Distillation in Federated Learning: A Survey on Long Lasting Challenges and New Solutions. Int. J. Intell. Syst. 2025(1) (2025) - [j652]Chaoguang Luo, Liuying Wen, Yong Qin, Philip S. Yu, Liangwei Yang, Zhineng Hu:
Diversified recommendation with weighted hypergraph embedding: Case study in music. Neurocomputing 616: 128905 (2025) - [j651]Litian Zhang, Xiaoming Zhang, Ziyi Zhou, Xi Zhang, Philip S. Yu, Chaozhuo Li:
Knowledge-aware multimodal pre-training for fake news detection. Inf. Fusion 114: 102715 (2025) - [j650]Jia-Hao Syu, Jerry Chun-Wei Lin, Philip S. Yu:
Multi-head learning models for power consumption prediction of unmanned ground vehicles. Inf. Fusion 118: 102895 (2025) - [j649]Qihua Feng, Zhixun Lu, Chaozhuo Li, Feiran Huang, Jian Weng, Philip S. Yu:
End-to-end privacy-preserving image retrieval in cloud computing via anti-perturbation attentive token-aware vision transformer. Inf. Fusion 121: 103153 (2025) - [j648]Lixiang Xu, Kang Jiang, Xin Niu, Enhong Chen, Bin Luo, Philip S. Yu:
GL-BKGNN: Graphlet-based Bi-Kernel Interpretable Graph Neural Networks. Inf. Fusion 123: 103284 (2025) - [j647]Tie Li, Gang Kou, Yi Peng, Philip S. Yu:
Feature Selection and Grouping Effect Analysis for Credit Evaluation via Regularized Diagonal Distance Metric Learning. INFORMS J. Comput. 37(5): 1391-1412 (2025) - [j646]Hengzhu Liu, Ping Xiong, Tianqing Zhu, Philip S. Yu:
A survey on machine unlearning: Techniques and new emerged privacy risks. J. Inf. Secur. Appl. 90: 104010 (2025) - [j645]Chunkai Zhang, Yao Lu, Yuting Yang, Ryan Han-Yuan Zhang, Wensheng Gan, Philip S. Yu:
Mining high utility contrast patterns in sequences. Knowl. Inf. Syst. 67(11): 9947-9985 (2025) - [j644]Han Chen, Hairong Wang, Zhipeng Liu, Yuhua Li, Yifan Hu, Yujing Zhang, Kai Shu, Ruixuan Li, Philip S. Yu:
Multi-modal Robustness Fake News Detection with Cross-Modal and Propagation Network Contrastive Learning. Knowl. Based Syst. 309: 112800 (2025) - [j643]Jiayang Wu, Wensheng Gan, Jiahao Zhang, Philip S. Yu:
Contrastive learning for anomaly detection in hierarchical subgraph. Knowl. Based Syst. 317: 113435 (2025) - [j642]Junsan Zhang, Yuxue Liu, Mingwen Shao, Chenglizhao Chen, Zixuan Wang, Junliang Li, Yao Wan, Philip S. Yu:
Dual-level semantic collaboration and inference network for medical image report generation. Knowl. Based Syst. 328: 114278 (2025) - [j641]Yanxin Zheng, Wensheng Gan, Zefeng Chen, Zhenlian Qi, Qian Liang, Philip S. Yu:
Large language models for medicine: a survey. Int. J. Mach. Learn. Cybern. 16(2): 1015-1040 (2025) - [j640]Hong Lin, Wensheng Gan, Gengsen Huang, Philip S. Yu:
Towards high-utility sequential rules with repetitive items. Int. J. Mach. Learn. Cybern. 16(10): 7729-7745 (2025) - [j639]Ce Zhou, Qian Li, Chen Li, Jun Yu, Yixin Liu, Guangjing Wang, Kai Zhang, Cheng Ji, Qiben Yan, Lifang He, Hao Peng, Jianxin Li, Jia Wu, Ziwei Liu, Pengtao Xie, Caiming Xiong, Jian Pei, Philip S. Yu, Lichao Sun:
A comprehensive survey on pretrained foundation models: a history from BERT to ChatGPT. Int. J. Mach. Learn. Cybern. 16(12): 9851-9915 (2025) - [j638]Fanlong Zeng, Wensheng Gan, Yongheng Wang, Philip S. Yu:
Distributed training of large language models: A survey. Nat. Lang. Process. J. 12: 100174 (2025) - [j637]Runliang Niu, Qi Wang, He Kong, Qianli Xing, Yi Chang, Philip S. Yu:
Learn to explain transformer via interpretation path by reinforcement learning. Neural Networks 188: 107496 (2025) - [j636]Xiaoyan Yu, Jiaqian Ren, Lei Jiang, Hao Peng, Zhifeng Hao, Li Sun, Kun Peng, Liehuang Zhu, Philip S. Yu:
PromptSED: An evolving topic-enhanced prompting framework for incremental social event detection. Neural Networks 191: 107772 (2025) - [j635]Linlin Wang, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Linkage on security, privacy and fairness in federated learning: New balances and new perspectives. Neural Networks 192: 107874 (2025) - [j634]Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi:
Graph Foundation Models: Concepts, Opportunities and Challenges. IEEE Trans. Pattern Anal. Mach. Intell. 47(6): 5023-5044 (2025) - [j633]Libo Qin, Qiguang Chen, Yuhang Zhou, Zhi Chen, Yinghui Li, Lizi Liao, Min Li, Wanxiang Che, Philip S. Yu:
A survey of multilingual large language models. Patterns 6(1): 101118 (2025) - [j632]Lixiang Xu, Zhiwen Wang, Lu Bai, Shengwei Ji, Bing Ai, Xiaofeng Wang, Philip S. Yu:
Multi-Level Knowledge Distillation with Positional Encoding Enhancement. Pattern Recognit. 163: 111458 (2025) - [j631]Qian Ma, Hongliang Chi, Hengrui Zhang, Kay Liu, Zhiwei Zhang, Lu Cheng, Suhang Wang, Philip S. Yu, Yao Ma:
Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks. SIGKDD Explor. 27(2): 97-106 (2025) - [j630]Shen Wang, Tianlong Xu, Hang Li, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, Qingsong Wen:
Large Language Models for Education: A survey and outlook. IEEE Signal Process. Mag. 42(6): 51-63 (2025) - [j629]Jiayang Wu, Wensheng Gan, Jiahao Zhang, Philip S. Yu:
ADKGD: Anomaly Detection in Knowledge Graphs with Dual-Channel Training. ACM Trans. Asian Low Resour. Lang. Inf. Process. 24(11): 122:1-122:29 (2025) - [j628]Heng Xu, Tianqing Zhu, Lefeng Zhang, Wanlei Zhou, Philip S. Yu:
Update Selective Parameters: Federated Machine Unlearning Based on Model Explanation. IEEE Trans. Big Data 11(2): 524-539 (2025) - [j627]Huiqiang Chen, Tianqing Zhu, Bo Liu, Wanlei Zhou, Philip S. Yu:
Fine-Tuning a Biased Model for Improving Fairness. IEEE Trans. Big Data 11(3): 1397-1410 (2025) - [j626]Huan Tian, Bo Liu, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Distilling Fair Representations From Fair Teachers. IEEE Trans. Big Data 11(3): 1419-1433 (2025) - [j625]Faqian Guan, Tianqing Zhu, Hui Sun, Wanlei Zhou, Philip S. Yu:
Large Language Models for Link Stealing Attacks Against Graph Neural Networks. IEEE Trans. Big Data 11(4): 1879-1893 (2025) - [j624]Faqian Guan, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Topology-Based Node-Level Membership Inference Attacks on Graph Neural Networks. IEEE Trans. Big Data 11(5): 2809-2826 (2025) - [j623]Xiao-Dong Huang, Ling Huang, Yuefang Gao, Zhe-Yuan Li, Pei-Yuan Lai, Chang-Dong Wang, Philip S. Yu:
Knowledge-Aware Graph Prompt Tuning for Cross-Domain Recommendation. IEEE Trans. Comput. Soc. Syst. 12(6): 3923-3937 (2025) - [j622]Jian Zhu, Xiaoye Chen, Wensheng Gan, Zefeng Chen, Philip S. Yu:
Targeted Mining Precise-Positioning Episode Rules. IEEE Trans. Emerg. Top. Comput. Intell. 9(1): 904-917 (2025) - [j621]Zhi Li, Chaozhuo Li, Feiran Huang, Xi Zhang, Jian Weng, Philip S. Yu:
LapGLP: Approximating Infinite-Layer Graph Convolutions With Laplacian for Federated Recommendation. IEEE Trans. Inf. Forensics Secur. 20: 8178-8193 (2025) - [j620]Jiayang Wu, Wensheng Gan, Huashen Lu, Philip S. Yu:
Graph Contrastive Learning on Multi-label Classification for Recommendations. ACM Trans. Intell. Syst. Technol. 16(4): 77:1-77:19 (2025) - [j619]Zhixiao Wang, Jiayu Zhao, Chengcheng Sun, Xiaobin Rui, Philip S. Yu:
A General Concave Fairness Framework for Influence Maximization Based on Poverty Reward. ACM Trans. Knowl. Discov. Data 19(1): 14:1-14:23 (2025) - [j618]Hao Yan, Senzhang Wang, Chaozhuo Li, Jun Yin, Philip S. Yu, Jianxin Wang:
Have Our Cake and Eat It: Augmentation Diversity and Semantic Consistency Balanced Graph Contrastive Learning. ACM Trans. Knowl. Discov. Data 19(4): 1-25 (2025) - [j617]Jin-Jie Qiu, Shengda Zhuo, Philip S. Yu, Chang-Dong Wang, Shuqiang Huang:
Online Learning for Noisy Labeled Streams. ACM Trans. Knowl. Discov. Data 19(6): 1-29 (2025) - [j616]Gengsen Huang, Wensheng Gan, Philip S. Yu:
Towards Sequence Utility Maximization under Utility Occupancy Measure. ACM Trans. Knowl. Discov. Data 19(7): 126:1-126:27 (2025) - [j615]Guangjie Zeng, Hao Peng, Angsheng Li, Jia Wu, Chunyang Liu, Philip S. Yu:
Scalable Semi-Supervised Clustering via Structural Entropy With Different Constraints. IEEE Trans. Knowl. Data Eng. 37(1): 478-492 (2025) - [j614]Litian Zhang, Xiaoming Zhang, Ziyi Zhou, Xi Zhang, Senzhang Wang, Philip S. Yu, Chaozhuo Li:
Early Detection of Multimodal Fake News via Reinforced Propagation Path Generation. IEEE Trans. Knowl. Data Eng. 37(2): 613-625 (2025) - [j613]Runze Yang, Hao Peng, Angsheng Li, Peng Li, Chunyang Liu, Philip S. Yu:
Hierarchical Abstracting Graph Kernel. IEEE Trans. Knowl. Data Eng. 37(2): 724-738 (2025) - [j612]Zeyu Zhang, Chaozhuo Li, Xu Chen, Xing Xie, Philip S. Yu:
Meta Recommendation With Robustness Improvement. IEEE Trans. Knowl. Data Eng. 37(2): 781-793 (2025) - [j611]Lu Bai, Lixin Cui, Ming Li, Peng Ren, Yue Wang, Lichi Zhang, Philip S. Yu, Edwin R. Hancock:
AEGK: Aligned Entropic Graph Kernels Through Continuous-Time Quantum Walks. IEEE Trans. Knowl. Data Eng. 37(3): 1064-1078 (2025) - [j610]Ya-Wen Teng, Yishuo Shi, De-Nian Yang, Chih-Hua Tai, Philip S. Yu, Ming-Syan Chen:
Multi-Grade Revenue Maximization for Promotional and Competitive Viral Marketing in Social Networks. IEEE Trans. Knowl. Data Eng. 37(3): 1339-1353 (2025) - [j609]Juyong Jiang, Peiyan Zhang, Yingtao Luo, Chaozhuo Li, Jae Boum Kim, Kai Zhang, Senzhang Wang, Sunghun Kim, Philip S. Yu:
Improving Sequential Recommendations via Bidirectional Temporal Data Augmentation With Pre-Training. IEEE Trans. Knowl. Data Eng. 37(5): 2652-2664 (2025) - [j608]Songwei Zhao, Bo Yu, Kang Yang, Sinuo Zhang, Jifeng Hu, Yuan Jiang, Philip S. Yu, Hechang Chen:
A Flexible Diffusion Convolution for Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 37(6): 3118-3131 (2025) - [j607]Wensheng Gan, Gengsen Huang, Jian Weng, Tianlong Gu, Philip S. Yu:
Towards Target Sequential Rules. IEEE Trans. Knowl. Data Eng. 37(6): 3766-3780 (2025) - [j606]Xiaobin Rui, Zhixiao Wang, Hao Peng, Wei Chen, Philip S. Yu:
A Scalable Algorithm for Fair Influence Maximization With Unbiased Estimator. IEEE Trans. Knowl. Data Eng. 37(7): 3881-3895 (2025) - [j605]Zhangtao Cheng, Yang Liu, Ting Zhong, Kunpeng Zhang, Fan Zhou, Philip S. Yu:
Disentangling Inter- and Intra-Cascades Dynamics for Information Diffusion Prediction. IEEE Trans. Knowl. Data Eng. 37(8): 4548-4563 (2025) - [j604]Qitong Liu, Hao Peng, Xiang Huang, Zhifeng Hao, Qingyun Sun, Zhengtao Yu, Philip S. Yu:
Hierarchical Text Classification Optimization via Structural Entropy and Singular Smoothing. IEEE Trans. Knowl. Data Eng. 37(9): 5283-5297 (2025) - [j603]Songwei Zhao, Bo Yu, Sinuo Zhang, Zhejian Yang, Jifeng Hu, Philip S. Yu, Hechang Chen:
EGNN: Exploring Structure-Level Neighborhoods in Graphs With Varying Homophily Ratios. IEEE Trans. Knowl. Data Eng. 37(10): 5852-5865 (2025) - [j602]Hao Miao, Ronghui Xu, Yan Zhao, Senzhang Wang, Jianxin Wang, Philip S. Yu, Christian S. Jensen:
A Parameter-Efficient Federated Framework for Streaming Time Series Anomaly Detection via Lightweight Adaptation. IEEE Trans. Mob. Comput. 24(9): 8872-8885 (2025) - [j601]Zefeng Chen, Wensheng Gan, Gengsen Huang, Zhenlian Qi, Yan Li, Philip S. Yu:
TALENT: Targeted Mining of Non-overlapping Sequential Patterns. ACM Trans. Manag. Inf. Syst. 16(4): 31:1-31:34 (2025) - [j600]Wenjing Chang, Kay Liu, Philip S. Yu, Jianjun Yu:
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement. Trans. Mach. Learn. Res. 2025 (2025) - [j599]Haoyan Xu, Kay Liu, Zhengtao Yao, Philip S. Yu, Mengyuan Li, Kaize Ding, Yue Zhao:
LEGO-Learn: Label-Efficient Graph Open-Set Learning. Trans. Mach. Learn. Res. 2025 (2025) - [j598]Huan Tian, Bo Liu, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
MultiFair: Model Fairness With Multiple Sensitive Attributes. IEEE Trans. Neural Networks Learn. Syst. 36(3): 5654-5667 (2025) - [j597]Yazhou Ren, Jingyu Pu, Zhimeng Yang, Jie Xu, Guofeng Li, Xiaorong Pu, Philip S. Yu, Lifang He:
Deep Clustering: A Comprehensive Survey. IEEE Trans. Neural Networks Learn. Syst. 36(4): 5858-5878 (2025) - [j596]Xusheng Zhao, Qiong Dai, Xu Bai, Jia Wu, Hao Peng, Huailiang Peng, Zhengtao Yu, Philip S. Yu:
Reinforced GNNs for Multiple Instance Learning. IEEE Trans. Neural Networks Learn. Syst. 36(4): 6693-6707 (2025) - [j595]Phu Pham, Quang-Thinh Bui, Ngoc Thanh Nguyen, Robert Kozma, Philip S. Yu, Bay Vo:
Topological Data Analysis in Graph Neural Networks: Surveys and Perspectives. IEEE Trans. Neural Networks Learn. Syst. 36(6): 9758-9776 (2025) - [j594]Jianpeng Chen, Yawen Ling, Jie Xu, Yazhou Ren, Shudong Huang, Xiaorong Pu, Zhifeng Hao, Philip S. Yu, Lifang He:
Variational Graph Generator for Multiview Graph Clustering. IEEE Trans. Neural Networks Learn. Syst. 36(6): 11078-11091 (2025) - [j593]Ling Huang, Dong Huang, Han Zou, Yuefang Gao, Chang-Dong Wang, Philip S. Yu:
Knowledge-Reinforced Cross-Domain Recommendation. IEEE Trans. Neural Networks Learn. Syst. 36(7): 12880-12894 (2025) - [j592]Zheng Wang, Hongming Ding, Li Pan, Jianhua Li, Zhiguo Gong, Philip S. Yu:
From Cluster Assumption to Graph Convolution: Graph-Based Semi-Supervised Learning Revisited. IEEE Trans. Neural Networks Learn. Syst. 36(7): 12952-12963 (2025) - [j591]Xiaoye Chen, Wensheng Gan, Zefeng Chen, Jian Zhu, Ruichu Cai, Philip S. Yu:
Toward Targeted Mining of RFM Patterns. IEEE Trans. Neural Networks Learn. Syst. 36(9): 16619-16632 (2025) - [j590]Pu Li, Xiaoyan Yu, Hao Peng, Yantuan Xian, Linqin Wang, Li Sun, Jingyun Zhang, Philip S. Yu:
Relational Prompt-Based Pre-Trained Language Models for Social Event Detection. ACM Trans. Inf. Syst. 43(1): 12:1-12:43 (2025) - [j589]Zhiwei Liu, Hao Peng, Caiming Xiong, Julian J. McAuley, Philip S. Yu:
Introduction to the Special Issue on Knowledge Transferring for Recommender Systems. Trans. Recomm. Syst. 3(3): 26:1-26:4 (2025) - [j588]Qihua Feng, Zhixun Lu, Litian Zhang, Chaozhuo Li, Feiran Huang, Jian Weng, Philip S. Yu:
Privacy-Preserving Image Retrieval in Cloud Computing via Adaptive Secret Keys and Self-Supervised Block-Augmented Pretraining. IEEE Trans. Serv. Comput. 18(4): 2310-2325 (2025) - [j587]Yang Wu, Yao Wan, Zhaoyang Chu, Wenting Zhao, Ye Liu, Hongyu Zhang, Xuanhua Shi, Hai Jin, Philip S. Yu:
Can Large Language Models Serve as Evaluators for Code Summarization? IEEE Trans. Software Eng. 51(12): 3205-3217 (2025) - [c1178]Li Sun, Ziheng Zhang, Zixi Wang, Yujie Wang, Qiqi Wan, Hao Li, Hao Peng, Philip S. Yu:
Pioneer: Physics-informed Riemannian Graph ODE for Entropy-increasing Dynamics. AAAI 2025: 12586-12594 - [c1177]Xiaoyan Yu, Yifan Wei, Shuaishuai Zhou, Zhiwei Yang, Li Sun, Hao Peng, Liehuang Zhu, Philip S. Yu:
Towards Effective, Efficient and Unsupervised Social Event Detection in the Hyperbolic Space. AAAI 2025: 13106-13114 - [c1176]Xiang Huang, Hao Peng, Li Sun, Hui Lin, Chunyang Liu, Jiang Cao, Philip S. Yu:
Structural Entropy Guided Probabilistic Coding. AAAI 2025: 17467-17475 - [c1175]Yibo Yan, Shen Wang, Jiahao Huo, Philip S. Yu, Xuming Hu, Qingsong Wen:
MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection. ACL (6) 2025: 69-82 - [c1174]Yinghui Li, Shang Qin, Jingheng Ye, Haojing Huang, Yangning Li, Shu-Yu Guo, Libo Qin, Xuming Hu, Wenhao Jiang, Hai-Tao Zheng, Philip S. Yu:
Rethinking the Roles of Large Language Models in Chinese Grammatical Error Correction. ACL (6) 2025: 553-567 - [c1173]Xiuxuan Shen, Zhongyuan Jiang, Junsan Zhang, Junxiao Han, Yao Wan, Chengjie Guo, Bingcheng Liu, Jie Wu, Renxiang Li, Philip S. Yu:
ProvBench: A Benchmark of Legal Provision Recommendation for Contract Auto-Reviewing. ACL (1) 2025: 6240-6254 - [c1172]Lingwei Wei, Dou Hu, Wei Zhou, Philip S. Yu, Songlin Hu:
Structure-adaptive Adversarial Contrastive Learning for Multi-Domain Fake News Detection. ACL (Findings) 2025: 9739-9752 - [c1171]