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ORCIDPhilip S. Yu
Person information
- 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
- 2024
[j566]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)- [j565]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) - [j564]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) - [j563]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) - [j562]Yijie Gui, Wensheng Gan, Yongdong Wu, Philip S. Yu:
Privacy preserving rare itemset mining. Inf. Sci. 662: 120262 (2024) - [j561]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) - [j560]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) - [j559]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) - [j558]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) - [j557]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) - [j556]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) - [j555]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) - [j554]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) - [j553]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) - [j552]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) - [j551]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) - [j550]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) - [j549]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) - [j548]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) - [j547]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) - [j546]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) - [j545]Gengsen Huang, Wensheng Gan, Philip S. Yu:
TaSPM: Targeted Sequential Pattern Mining. ACM Trans. Knowl. Discov. Data 18(5): 114:1-114:18 (2024) - [j544]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) - [j543]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) - [j542]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) - [j541]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) - [j540]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) - [j539]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) - [j538]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) - [j537]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) - [j536]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) - [j535]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) - [j534]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) - [j533]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) - [j532]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) - [j531]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) - [j530]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) - [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) - [c1079]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 - [c1078]Yuwei Cao, Hao Peng, Zhengtao Yu, Philip S. Yu:
Hierarchical and Incremental Structural Entropy Minimization for Unsupervised Social Event Detection. AAAI 2024: 8255-8264 - [c1077]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 - [c1076]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 - [c1075]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 - [c1074]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 - [c1073]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 - [c1072]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 - [c1071]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 - [c1070]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 - [c1069]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 - [c1068]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 - [c1067]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 - [c1066]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 - [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]Zefeng Chen, Wensheng Gan, Jiayi Sun, Jiayang Wu, Philip S. Yu:
Open Metaverse: Issues, Evolution, and Future. WWW (Companion Volume) 2024: 1351-1360 - [c1050]Wenting Zhao, Zhongfen Deng, Shweta Yadav, Philip S. Yu:
Heterogeneous Knowledge Grounding for Medical Question Answering with Retrieval Augmented Large Language Model. WWW (Companion Volume) 2024: 1590-1594 - [c1049]Li Sun, Jingbin Hu, Suyang Zhou, Zhenhao Huang, Junda Ye, Hao Peng, Zhengtao Yu, Philip S. Yu:
RicciNet: Deep Clustering via A Riemannian Generative Model. WWW 2024: 4071-4082 - [i508]Yao Wan, Yang He, Zhangqian Bi, Jianguo Zhang, Hongyu Zhang, Yulei Sui, Guandong Xu, Hai Jin, Philip S. Yu:
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit. CoRR abs/2401.00288 (2024) - [i507]Li Sun, Zhenhao Huang, Zixi Wang, Feiyang Wang, Hao Peng, Philip S. Yu:
Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning. CoRR abs/2401.01232 (2024) - [i506]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. CoRR abs/2401.01243 (2024) - [i505]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, 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, 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, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i504]Li Sun, Zhenhao Huang, Hua Wu, Junda Ye, Hao Peng, Zhengtao Yu, Philip S. Yu:
DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing. CoRR abs/2401.12780 (2024) - [i503]Wenjing Chang, Kay Liu, Kaize Ding, Philip S. Yu, Jianjun Yu:
Multitask Active Learning for Graph Anomaly Detection. CoRR abs/2401.13210 (2024) - [i502]Liangwei Yang, Hengrui Zhang, Zihe Song, Jiawei Zhang, Weizhi Zhang, Jing Ma, Philip S. Yu:
Cyclic Neural Network. CoRR abs/2402.03332 (2024) - [i501]Yuqing Liu, Yu Wang, Lichao Sun, Philip S. Yu:
Rec-GPT4V: Multimodal Recommendation with Large Vision-Language Models. CoRR abs/2402.08670 (2024) - [i500]Chen Wang, Fangxin Wang, Ruocheng Guo, Yueqing Liang, Kay Liu, Philip S. Yu:
Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction. CoRR abs/2402.08976 (2024) - [i499]Yinghui Li, Qingyu Zhou, Yuanzhen Luo, Shirong Ma, Yangning Li, Hai-Tao Zheng, Xuming Hu, Philip S. Yu:
When LLMs Meet Cunning Questions: A Fallacy Understanding Benchmark for Large Language Models. CoRR abs/2402.11100 (2024) - [i498]Xiangjue Dong, Yibo Wang, Philip S. Yu, James Caverlee:
Disclosure and Mitigation of Gender Bias in LLMs. CoRR abs/2402.11190 (2024) - [i497]Yinghui Li, Shang Qin, Jingheng Ye, Shirong Ma, Yangning Li, Libo Qin, Xuming Hu, Wenhao Jiang, Hai-Tao Zheng, Philip S. Yu:
Rethinking the Roles of Large Language Models in Chinese Grammatical Error Correction. CoRR abs/2402.11420 (2024) - [i496]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. CoRR abs/2402.15680 (2024) - [i495]Chaoguang Luo, Liuying Wen, Yong Qin, Liangwei Yang, Zhineng Hu, Philip S. Yu:
Against Filter Bubbles: Diversified Music Recommendation via Weighted Hypergraph Embedding Learning. CoRR abs/2402.16299 (2024) - [i494]Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Xiao Luo, Philip S. Yu, Ming Zhang:
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges. CoRR abs/2403.04468 (2024) - [i493]Fangxin Wang, Yuqing Liu, Kay Liu, Yibo Wang, Sourav Medya, Philip S. Yu:
Uncertainty in Graph Neural Networks: A Survey. CoRR abs/2403.07185 (2024) - [i492]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 Factual Questions. CoRR abs/2403.12077 (2024) - [i491]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. CoRR abs/2403.18105 (2024) - [i490]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Instruction-based Hypergraph Pretraining. CoRR abs/2403.19063 (2024) - [i489]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. CoRR abs/2403.19907 (2024) - [i488]Libo Qin, Qiguang Chen, Yuhang Zhou, Zhi Chen, Yinghui Li, Lizi Liao, Min Li, Wanxiang Che, Philip S. Yu:
Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers. CoRR abs/2404.04925 (2024) - [i487]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. CoRR abs/2404.08263 (2024) - [i486]Hoang H. 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. CoRR abs/2404.12618 (2024) - [i485]Hao Peng, Jingyun Zhang, Xiang Huang, Zhifeng Hao, Angsheng Li, Zhengtao Yu, Philip S. Yu:
Unsupervised Social Bot Detection via Structural Information Theory. CoRR abs/2404.13595 (2024) - [i484]Chao Chen, Chenghua Guo, Rui Xu, Xiangwen Liao, Xi Zhang, Sihong Xie, Hui Xiong, Philip S. Yu:
Uncertainty Quantification on Graph Learning: A Survey. CoRR abs/2404.14642 (2024) - [i483]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. CoRR abs/2404.15592 (2024) - [i482]Weizhi Zhang, Liangwei Yang, Zihe Song, Henry Peng Zou, Ke Xu, Yuanjie Zhu, Philip S. Yu:
Mixed Supervised Graph Contrastive Learning for Recommendation. CoRR abs/2404.15954 (2024) - [i481]Jiayang Wu, Wensheng Gan, Han-Chieh Chao, Philip S. Yu:
Geospatial Big Data: Survey and Challenges. CoRR abs/2404.18428 (2024) - [i480]Yuwei Cao, Hao Peng, Angsheng Li, Chenyu You, Zhifeng Hao, Philip S. Yu:
Multi-Relational Structural Entropy. CoRR abs/2405.07096 (2024) - [i479]Li Sun, Zhenhao Huang, Hao Peng, Yujie Wang, Chunyang Liu, Philip S. Yu:
LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering. CoRR abs/2405.11801 (2024) - [i478]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. CoRR abs/2405.12819 (2024) - [i477]Hanyi Xu, Wensheng Gan, Zhenlian Qi, Jiayang Wu, Philip S. Yu:
Large Language Models for Education: A Survey. CoRR abs/2405.13001 (2024) - [i476]Yanxin Zheng, Wensheng Gan, Zefeng Chen, Zhenlian Qi, Qian Liang, Philip S. Yu:
Large Language Models for Medicine: A Survey. CoRR abs/2405.13055 (2024) - [i475]Hengrui Zhang, Liancheng Fang, Philip S. Yu:
Unleashing the Potential of Diffusion Models for Incomplete Data Imputation. CoRR abs/2405.20690 (2024) - [i474]Wenjing Chang, Kay Liu, Philip S. Yu, Jianjun Yu:
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement. CoRR abs/2406.00987 (2024) - [i473]Ronghui Xu, Hao Miao, Senzhang Wang, Philip S. Yu, Jianxin Wang:
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Graph Neural Networks for Brain Graph Learning: A Survey. CoRR abs/2406.02594 (2024) - [i471]