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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
- 2025
[j587]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)- [j586]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) - [j585]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) - 2024
- [j584]Jinqi Lai, Wensheng Gan, Jiayang Wu, Zhenlian Qi, Philip S. Yu:
Large language models in law: A survey. AI Open 5: 181-196 (2024) - [j583]Heng Xu, Tianqing Zhu, Lefeng Zhang, Wanlei Zhou, Philip S. Yu:
Machine Unlearning: A Survey. ACM Comput. Surv. 56(1): 9:1-9:36 (2024) - [j582]Huiqiang Chen, Tianqing Zhu, Tao Zhang, Wanlei Zhou, Philip S. Yu:
Privacy and Fairness in Federated Learning: On the Perspective of Tradeoff. ACM Comput. Surv. 56(2): 39:1-39:37 (2024) - [j581]Yao Wan, Zhangqian Bi, Yang He, Jianguo Zhang, Hongyu Zhang, Yulei Sui, Guandong Xu, Hai Jin, Philip S. Yu:
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit. ACM Comput. Surv. 56(12): 309:1-309:41 (2024) - [j580]Xinqi Du, Hechang Chen, Yongheng Xing, Philip S. Yu, Lifang He:
A Contrastive-Enhanced Ensemble Framework for Efficient Multi-Agent Reinforcement Learning. Expert Syst. Appl. 245: 123158 (2024) - [j579]Yao Chen, Wensheng Gan, Gengsen Huang, Yongdong Wu, Philip S. Yu:
Privacy-preserving federated discovery of DNA motifs with differential privacy. Expert Syst. Appl. 249: 123799 (2024) - [j578]Liangqi Yuan, Ziran Wang, Lichao Sun, Philip S. Yu, Christopher G. Brinton:
Decentralized Federated Learning: A Survey and Perspective. IEEE Internet Things J. 11(21): 34617-34638 (2024) - [j577]Shicheng Wan, Hong Lin, Wensheng Gan, Jiahui Chen, Philip S. Yu:
Web3: The Next Internet Revolution. IEEE Internet Things J. 11(21): 34811-34825 (2024) - [j576]Yijie Gui, Wensheng Gan, Yongdong Wu, Philip S. Yu:
Privacy preserving rare itemset mining. Inf. Sci. 662: 120262 (2024) - [j575]Kay Liu, Yingtong Dou, Xueying Ding, Xiyang Hu, Ruitong Zhang, Hao Peng, Lichao Sun, Philip S. Yu:
PyGOD: A Python Library for Graph Outlier Detection. J. Mach. Learn. Res. 25: 141:1-141:9 (2024) - [j574]Zefeng Chen, Wensheng Gan, Gengsen Huang, Yanxin Zheng, Philip S. Yu:
Towards utility-driven contiguous sequential patterns in uncertain multi-sequences. Knowl. Based Syst. 284: 111314 (2024) - [j573]Han Chen, Yuhua Li, Philip S. Yu, Yixiong Zou, Ruixuan Li:
DCMSL: Dual influenced community strength-boosted multi-scale graph contrastive learning. Knowl. Based Syst. 304: 112472 (2024) - [j572]Hao Peng, Jia Wu, Jiaxu Cui, Philip S. Yu:
Introduction to the special issue on recent advances in graph learning: theory, algorithms, applications, and systems. Int. J. Mach. Learn. Cybern. 15(1): 1-2 (2024) - [j571]Li Sun, Junda Ye, Jiawei Zhang, Yong Yang, Mingsheng Liu, Feiyang Wang, Philip S. Yu:
Contrastive sequential interaction network learning on co-evolving Riemannian spaces. Int. J. Mach. Learn. Cybern. 15(4): 1397-1413 (2024) - [j570]Zhongyuan Jiang, Haibo Liu, Jing Li, Xinghua Li, Jianfeng Ma, Philip S. Yu:
Target link protection against link-prediction-based attacks via artificial bee colony algorithm based on random walk. Int. J. Mach. Learn. Cybern. 15(11): 4959-4971 (2024) - [j569]Guangsi Shi, Daokun Zhang, Ming Jin, Shirui Pan, Philip S. Yu:
Towards complex dynamic physics system simulation with graph neural ordinary equations. Neural Networks 176: 106341 (2024) - [j568]Qian Li, Jianxin Li, Jia Wu, Xutan Peng, Cheng Ji, Hao Peng, Lihong Wang, Philip S. Yu:
Triplet-aware graph neural networks for factorized multi-modal knowledge graph entity alignment. Neural Networks 179: 106479 (2024) - [j567]Lilin Zhang, Ning Yang, Yanchao Sun, Philip S. Yu:
Provable Unrestricted Adversarial Training Without Compromise With Generalizability. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 8302-8319 (2024) - [j566]Xinqi Du, Hechang Chen, Che Wang, Yongheng Xing, Jielong Yang, Philip S. Yu, Yi Chang, Lifang He:
Robust multi-agent reinforcement learning via Bayesian distributional value estimation. Pattern Recognit. 145: 109917 (2024) - [j565]Jiayang Wu, Wensheng Gan, Han-Chieh Chao, Philip S. Yu:
Geospatial Big Data: Survey and Challenges. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 17007-17020 (2024) - [j564]Jiushun Ma, Yuxin Huang, Linqin Wang, Xiang Huang, Hao Peng, Zhengtao Yu, Philip S. Yu:
Augmenting Low-Resource Cross-Lingual Summarization with Progression-Grounded Training and Prompting. ACM Trans. Asian Low Resour. Lang. Inf. Process. 23(9): 129:1-129:22 (2024) - [j563]Xiang Huang, Hao Peng, Dongcheng Zou, Zhiwei Liu, Jianxin Li, Kay Liu, Jia Wu, Jianlin Su, Philip S. Yu:
CoSENT: Consistent Sentence Embedding via Similarity Ranking. IEEE ACM Trans. Audio Speech Lang. Process. 32: 2800-2813 (2024) - [j562]Ran Song, Xiang Huang, Hao Peng, Shengxiang Gao, Zhengtao Yu, Philip S. Yu:
WDEA: The Structure and Semantic Fusion With Wasserstein Distance for Low-Resource Language Entity Alignment. IEEE ACM Trans. Audio Speech Lang. Process. 32: 4511-4525 (2024) - [j561]Linqin Wang, Xiang Huang, Zhengtao Yu, Hao Peng, Shengxiang Gao, Cunli Mao, Yuxin Huang, Ling Dong, Philip S. Yu:
Zero-Shot Text Normalization via Cross-Lingual Knowledge Distillation. IEEE ACM Trans. Audio Speech Lang. Process. 32: 4631-4646 (2024) - [j560]Senzhang Wang, Changdong Wang, Di Jin, Shirui Pan, Philip S. Yu:
Guest Editorial TBD Special Issue on Graph Machine Learning for Recommender Systems. IEEE Trans. Big Data 10(6): 682 (2024) - [j559]Qihua Feng, Peiya Li, Zhixun Lu, Chaozhuo Li, Zefan Wang, Zhiquan Liu, Chunhui Duan, Feiran Huang, Jian Weng, Philip S. Yu:
EViT: Privacy-Preserving Image Retrieval via Encrypted Vision Transformer in Cloud Computing. IEEE Trans. Circuits Syst. Video Technol. 34(8): 7467-7483 (2024) - [j558]Zhixiao Wang, Yahui Chai, Chengcheng Sun, Xiaobin Rui, Hao Mi, Xinyu Zhang, Philip S. Yu:
A Weighted Symmetric Graph Embedding Approach for Link Prediction in Undirected Graphs. IEEE Trans. Cybern. 54(2): 1037-1047 (2024) - [j557]Bin Pu, Jiansong Liu, Yan Kang, Jianguo Chen, Philip S. Yu:
MVSTT: A Multiview Spatial-Temporal Transformer Network for Traffic-Flow Forecasting. IEEE Trans. Cybern. 54(3): 1582-1595 (2024) - [j556]Jia Wu, Jian Yang, Philip S. Yu, Carlo Condo:
Special Section on Community Detection in Time-Varying Information and Computing Networks: Theory, Models, and Applications. IEEE Trans. Emerg. Top. Comput. 12(2): 402 (2024) - [j555]Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, Xing Xie:
A Survey on Evaluation of Large Language Models. ACM Trans. Intell. Syst. Technol. 15(3): 39:1-39:45 (2024) - [j554]Chunkai Zhang, Yuting Yang, Zilin Du, Wensheng Gan, Philip S. Yu:
HUSP-SP: Faster Utility Mining on Sequence Data. ACM Trans. Knowl. Discov. Data 18(1): 5:1-5:21 (2024) - [j553]Chunkai Zhang, Maohua Lyu, Wensheng Gan, Philip S. Yu:
Totally-ordered Sequential Rules for Utility Maximization. ACM Trans. Knowl. Discov. Data 18(4): 80:1-80:23 (2024) - [j552]Gengsen Huang, Wensheng Gan, Philip S. Yu:
TaSPM: Targeted Sequential Pattern Mining. ACM Trans. Knowl. Discov. Data 18(5): 114:1-114:18 (2024) - [j551]Ting-Ting Su, Chang-Dong Wang, Wu-Dong Xi, Jian-Huang Lai, Philip S. Yu:
Hierarchical Alignment With Polar Contrastive Learning for Next-Basket Recommendation. IEEE Trans. Knowl. Data Eng. 36(1): 199-210 (2024) - [j550]Chuanpan Zheng, Xiaoliang Fan, Shirui Pan, Haibing Jin, Zhaopeng Peng, Zonghan Wu, Cheng Wang, Philip S. Yu:
Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting. IEEE Trans. Knowl. Data Eng. 36(1): 372-385 (2024) - [j549]Yue Wang, Yao Wan, Lu Bai, Lixin Cui, Zhuo Xu, Ming Li, Philip S. Yu, Edwin R. Hancock:
Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus. IEEE Trans. Knowl. Data Eng. 36(2): 475-489 (2024) - [j548]Wen-Zhi Li, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
Towards Effective and Robust Graph Contrastive Learning With Graph Autoencoding. IEEE Trans. Knowl. Data Eng. 36(2): 868-881 (2024) - [j547]Siyuan Guo, Lixin Zou, Hechang Chen, Bohao Qu, Haotian Chi, Philip S. Yu, Yi Chang:
Sample Efficient Offline-to-Online Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 36(3): 1299-1310 (2024) - [j546]Xuming Hu, Zhaochen Hong, Chenwei Zhang, Aiwei Liu, Shiao Meng, Lijie Wen, Irwin King, Philip S. Yu:
Reading Broadly to Open Your Mind: Improving Open Relation Extraction With Search Documents Under Self-Supervisions. IEEE Trans. Knowl. Data Eng. 36(5): 2026-2040 (2024) - [j545]Shuaiqi Liu, Jiannong Cao, Zhongfen Deng, Wenting Zhao, Ruosong Yang, Zhiyuan Wen, Philip S. Yu:
Neural Abstractive Summarization for Long Text and Multiple Tables. IEEE Trans. Knowl. Data Eng. 36(6): 2572-2586 (2024) - [j544]Jiaqian Ren, Hao Peng, Lei Jiang, Zhiwei Liu, Jia Wu, Zhengtao Yu, Philip S. Yu:
Uncertainty-Guided Boundary Learning for Imbalanced Social Event Detection. IEEE Trans. Knowl. Data Eng. 36(6): 2701-2715 (2024) - [j543]Jiangnan Xia, Yu Yang, Senzhang Wang, Hongzhi Yin, Jiannong Cao, Philip S. Yu:
Bayes-Enhanced Multi-View Attention Networks for Robust POI Recommendation. IEEE Trans. Knowl. Data Eng. 36(7): 2895-2909 (2024) - [j542]Xinqi Du, Ziyue Li, Cheng Long, Yongheng Xing, Philip S. Yu, Hechang Chen:
FELight: Fairness-Aware Traffic Signal Control via Sample-Efficient Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 36(9): 4678-4692 (2024) - [j541]Man-Sheng Chen, Chang-Dong Wang, Dong Huang, Jian-Huang Lai, Philip S. Yu:
Concept Factorization Based Multiview Clustering for Large-Scale Data. IEEE Trans. Knowl. Data Eng. 36(11): 5784-5796 (2024) - [j540]Haibo Wang, Chuan Zhou, Xin Chen, Jia Wu, Shirui Pan, Zhao Li, Jilong Wang, Philip S. Yu:
Graph Structure Reshaping Against Adversarial Attacks on Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 36(11): 6344-6357 (2024) - [j539]Lu Bai, Lixin Cui, Yue Wang, Ming Li, Jing Li, Philip S. Yu, Edwin R. Hancock:
HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification. IEEE Trans. Knowl. Data Eng. 36(11): 6370-6384 (2024) - [j538]Yi Zhang, Yuying Zhao, Zhaoqing Li, Xueqi Cheng, Yu Wang, Olivera Kotevska, Philip S. Yu, Tyler Derr:
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications. IEEE Trans. Knowl. Data Eng. 36(12): 7497-7515 (2024) - [j537]Zhangtao Cheng, Fan Zhou, Xovee Xu, Kunpeng Zhang, Goce Trajcevski, Ting Zhong, Philip S. Yu:
Information Cascade Popularity Prediction via Probabilistic Diffusion. IEEE Trans. Knowl. Data Eng. 36(12): 8541-8555 (2024) - [j536]Tengfei Ma, Yujie Chen, Wen Tao, Dashun Zheng, Xuan Lin, Patrick Cheong-Iao Pang, Yiping Liu, Yijun Wang, Longyue Wang, Bosheng Song, Xiangxiang Zeng, Philip S. Yu:
Learning to Denoise Biomedical Knowledge Graph for Robust Molecular Interaction Prediction. IEEE Trans. Knowl. Data Eng. 36(12): 8682-8694 (2024) - [j535]Youwei Liang, Dong Huang, Chang-Dong Wang, Philip S. Yu:
Multi-View Graph Learning by Joint Modeling of Consistency and Inconsistency. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2848-2862 (2024) - [j534]Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, Philip S. Yu:
A Comprehensive Survey on Community Detection With Deep Learning. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4682-4702 (2024) - [j533]Qian Li, Jianxin Li, Jiawei Sheng, Shiyao Cui, Jia Wu, Yiming Hei, Hao Peng, Shu Guo, Lihong Wang, Amin Beheshti, Philip S. Yu:
A Survey on Deep Learning Event Extraction: Approaches and Applications. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6301-6321 (2024) - [j532]Lingjuan Lyu, Han Yu, Xingjun Ma, Chen Chen, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu:
Privacy and Robustness in Federated Learning: Attacks and Defenses. IEEE Trans. Neural Networks Learn. Syst. 35(7): 8726-8746 (2024) - [j531]Xunxun Wu, Chang-Dong Wang, Jia-Qi Lin, Wu-Dong Xi, Philip S. Yu:
Motif-Based Contrastive Learning for Community Detection. IEEE Trans. Neural Networks Learn. Syst. 35(9): 11706-11719 (2024) - [j530]Jie Xu, Chaozhuo Li, Feiran Huang, Zhoujun Li, Xing Xie, Philip S. Yu:
Sinkhorn Distance Minimization for Adaptive Semi-Supervised Social Network Alignment. IEEE Trans. Neural Networks Learn. Syst. 35(10): 13340-13353 (2024) - [j529]Hao Peng, Jian Yang, Jia Wu, Philip S. Yu:
Introduction to the Special Issue on Advanced Graph Mining on the Web: Theory, Algorithms, and Applications: Part 2. ACM Trans. Web 18(2): 16:1-16:2 (2024) - [c1091]Xiaorui Su, Pengwei Hu, Zhu-Hong You, Philip S. Yu, Lun Hu:
Dual-Channel Learning Framework for Drug-Drug Interaction Prediction via Relation-Aware Heterogeneous Graph Transformer. AAAI 2024: 249-256 - [c1090]Yuwei Cao, Hao Peng, Zhengtao Yu, Philip S. Yu:
Hierarchical and Incremental Structural Entropy Minimization for Unsupervised Social Event Detection. AAAI 2024: 8255-8264 - [c1089]Li Sun, Zhenhao Huang, Zixi Wang, Feiyang Wang, Hao Peng, Philip S. Yu:
Motif-Aware Riemannian Graph Neural Network with Generative-Contrastive Learning. AAAI 2024: 9044-9052 - [c1088]Jingyu Pu, Chenhang Cui, Xinyue Chen, Yazhou Ren, Xiaorong Pu, Zhifeng Hao, Philip S. Yu, Lifang He:
Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-View Clustering. AAAI 2024: 14633-14641 - [c1087]Xuming Hu, Zhaochen Hong, Yong Jiang, Zhichao Lin, Xiaobin Wang, Pengjun Xie, Philip S. Yu:
Three Heads Are Better than One: Improving Cross-Domain NER with Progressive Decomposed Network. AAAI 2024: 18261-18269 - [c1086]Henry Peng Zou, Vinay Samuel, Yue Zhou, Weizhi Zhang, Liancheng Fang, Zihe Song, Philip S. Yu, Cornelia Caragea:
ImplicitAVE: An Open-Source Dataset and Multimodal LLMs Benchmark for Implicit Attribute Value Extraction. ACL (Findings) 2024: 338-354 - [c1085]Tao Zhang, Chenwei Zhang, Xian Li, Jingbo Shang, Hoang Nguyen, Philip S. Yu:
Stronger, Lighter, Better: Towards Life-Long Attribute Value Extraction for E-Commerce Products. ACL (Findings) 2024: 8631-8643 - [c1084]Xuming Hu, Xiaochuan Li, Junzhe Chen, Yinghui Li, Yangning Li, Xiaoguang Li, Yasheng Wang, Qun Liu, Lijie Wen, Philip S. Yu, Zhijiang Guo:
Evaluating Robustness of Generative Search Engine on Adversarial Factoid Questions. ACL (Findings) 2024: 10650-10671 - [c1083]Zehao Gu, Shiyang Zhou, Yun Xiong, Yang Luo, Hongrun Ren, Qiang Wang, Xiaofeng Gao, Philip S. Yu:
MSTEM: Masked Spatiotemporal Event Series Modeling for Urban Undisciplined Events Forecasting. CIKM 2024: 685-694 - [c1082]Chen Wang, Liangwei Yang, Zhiwei Liu, Xiaolong Liu, Mingdai Yang, Yueqing Liang, Philip S. Yu:
Collaborative Alignment for Recommendation. CIKM 2024: 2315-2325 - [c1081]Xiaoyan Yu, Yifan Wei, Pu Li, Shuaishuai Zhou, Hao Peng, Li Sun, Liehuang Zhu, Philip S. Yu:
DAMe: Personalized Federated Social Event Detection with Dual Aggregation Mechanism. CIKM 2024: 3052-3062 - [c1080]Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu:
Revisit Orthogonality in Graph-Regularized MLPs. CIKM 2024: 3145-3154 - [c1079]Hengrui Zhang, Qitian Wu, Chenxiao Yang, Philip S. Yu:
InfoMLP: Unlocking the Potential of MLPs for Semi-Supervised Learning with Structured Data. CIKM 2024: 3155-3164 - [c1078]Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Liancheng Fang, Philip S. Yu:
Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation. CIKM 2024: 3248-3258 - [c1077]Luyi Ma, Xiaohan Li, Kamilia Ahmadi, Jianpeng Xu, Philip S. Yu, George Karypis:
3rd International Workshop on Industrial Recommendation Systems (IRS). CIKM 2024: 5588-5591 - [c1076]Yongfeng Zhang, Zhiwei Liu, Qingsong Wen, Linsey Pang, Wei Liu, Philip S. Yu:
AI Agent for Information Retrieval: Generating and Ranking. CIKM 2024: 5605-5607 - [c1075]Hoang Nguyen, Chenwei Zhang, Ye Liu, Natalie Parde, Eugene Rohrbaugh, Philip S. Yu:
CORI: CJKV Benchmark with Romanization Integration - a Step towards Cross-lingual Transfer beyond Textual Scripts. LREC/COLING 2024: 4008-4020 - [c1074]Yucheng Jin, Yun Xiong, Juncheng Fang, Xixi Wu, Dongxiao He, Xing Jia, Bingchen Zhao, Philip S. Yu:
Beyond the Known: Novel Class Discovery for Open-World Graph Learning. DASFAA (6) 2024: 117-133 - [c1073]Yibo Wang, Xiangjue Dong, James Caverlee, Philip S. Yu:
DA³: A Distribution-Aware Adversarial Attack against Language Models. EMNLP 2024: 1808-1825 - [c1072]Jiangshu Du, Yibo Wang, Wenting Zhao, Zhongfen Deng, Shuaiqi Liu, Renze Lou, Henry Peng Zou, Pranav Narayanan Venkit, Nan Zhang, Mukund Srinath, Haoran Zhang, Vipul Gupta, Yinghui Li, Tao Li, Fei Wang, Qin Liu, Tianlin Liu, Pengzhi Gao, Congying Xia, Chen Xing, Cheng Jiayang, Zhaowei Wang, Ying Su, Raj Sanjay Shah, Ruohao Guo, Jing Gu, Haoran Li, Kangda Wei, Zihao Wang, Lu Cheng, Surangika Ranathunga, Meng Fang, Jie Fu, Fei Liu, Ruihong Huang, Eduardo Blanco, Yixin Cao, Rui Zhang, Philip S. Yu, Wenpeng Yin:
LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing. EMNLP 2024: 5081-5099 - [c1071]Xuming Hu, Junzhe Chen, Xiaochuan Li, Yufei Guo, Lijie Wen, Philip S. Yu, Zhijiang Guo:
Towards Understanding Factual Knowledge of Large Language Models. ICLR 2024 - [c1070]Aiwei Liu, Leyi Pan, Xuming Hu, Shuang Li, Lijie Wen, Irwin King, Philip S. Yu:
An Unforgeable Publicly Verifiable Watermark for Large Language Models. ICLR 2024 - [c1069]Li Sun, Zhenhao Huang, Hao Peng, Yujie Wang, Chunyang Liu, Philip S. Yu:
LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering. ICML 2024 - [c1068]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c1067]Fariba Lotfi, Amin Beheshti, Mansour Jamzad, Hamid Beigy, Jia Wu, Philip S. Yu:
The Open Story Model (OSM): Transforming Big Data into Interactive Narratives. ICWS 2024: 1177-1187 - [c1066]Xuexiong Luo, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Quan Z. Sheng, David McAlpine, Paul F. Sowman, Alexis Giral, Philip S. Yu:
Graph Neural Networks for Brain Graph Learning: A Survey. IJCAI 2024: 8170-8178 - [c1065]Zhongyi Pei, Zhiyao Cen, Yipeng Huang, Chen Wang, Lin Liu, Philip S. Yu, Mingsheng Long, Jianmin Wang:
BTTackler: A Diagnosis-based Framework for Efficient Deep Learning Hyperparameter Optimization. KDD 2024: 2340-2351 - [c1064]Chen Wang, Ziwei Fan, Liangwei Yang, Mingdai Yang, Xiaolong Liu, Zhiwei Liu, Philip S. Yu:
Pre-Training with Transferable Attention for Addressing Market Shifts in Cross-Market Sequential Recommendation. KDD 2024: 2970-2979 - [c1063]Ronghui Xu, Hao Miao, Senzhang Wang, Philip S. Yu, Jianxin Wang:
PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detection. KDD 2024: 3621-3632 - [c1062]Yuxuan Liang, Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson:
The 13th International Workshop on Urban Computing. KDD 2024: 6727-6728 - [c1061]Wenting Zhao, Ye Liu, Tong Niu, Yao Wan, Philip S. Yu, Shafiq Joty, Yingbo Zhou, Semih Yavuz:
DIVKNOWQA: Assessing the Reasoning Ability of LLMs via Open-Domain Question Answering over Knowledge Base and Text. NAACL-HLT (Findings) 2024: 51-68 - [c1060]Wenting Zhao, Ye Liu, Yao Wan, Yibo Wang, Qingyang Wu, Zhongfen Deng, Jiangshu Du, Shuaiqi Liu, Yunlong Xu, Philip S. Yu:
kNN-ICL: Compositional Task-Oriented Parsing Generalization with Nearest Neighbor In-Context Learning. NAACL-HLT 2024: 326-337 - [c1059]Yu Wang, Zhiwei Liu, Liangwei Yang, Philip S. Yu:
Conditional Denoising Diffusion for Sequential Recommendation. PAKDD (5) 2024: 156-169 - [c1058]Kun Peng, Lei Jiang, Hao Peng, Rui Liu, Zhengtao Yu, Jiaqian Ren, Zhifeng Hao, Philip S. Yu:
Prompt Based Tri-Channel Graph Convolution Neural Network for Aspect Sentiment Triplet Extraction. SDM 2024: 145-153 - [c1057]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Instruction-based Hypergraph Pretraining. SIGIR 2024: 501-511 - [c1056]Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Mingdai Yang, Chen Wang, Hao Peng, Philip S. Yu:
Knowledge Graph Context-Enhanced Diversified Recommendation. WSDM 2024: 462-471 - [c1055]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Unified Pretraining for Recommendation via Task Hypergraphs. WSDM 2024: 891-900 - [c1054]Xusheng Zhao, Hao Peng, Qiong Dai, Xu Bai, Huailiang Peng, Yanbing Liu, Qinglang Guo, Philip S. Yu:
RDGCN: Reinforced Dependency Graph Convolutional Network for Aspect-based Sentiment Analysis. WSDM 2024: 976-984 - [c1053]Yue Huang, Kai Shu, Philip S. Yu, Lichao Sun:
From Creation to Clarification: ChatGPT's Journey Through the Fake News Quagmire. WWW (Companion Volume) 2024: 513-516 - [c1052]Chuan Shi, Cheng Yang, Yuan Fang, Lichao Sun, Philip S. Yu:
Lecture-style Tutorial: Towards Graph Foundation Models. WWW (Companion Volume) 2024: 1264-1267 - [c1051]