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ORCIDJie Tang 0001
唐杰
Person information
- unicode name: 唐杰
- affiliation: Tsinghua University, Department of Computer Science and Technology, Beijing, China
Other persons with the same name
- Jie Tang — disambiguation page
- Jie Tang 0002
![[0000-0003-0619-0338]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-0619-0338")
— South China University of Technology, School of Electronic and Information Engineering, Guangzhou, China (and 2 more) - Jie Tang 0003 — South China University of Technology, School of Computer Science and Engineering, Guangzhou, China (and 2 more)
- Jie Tang 0004 — Chinese Academy of Sciences, Shanghai Advanced Research Institute, China
- Jie Tang 0005 (aka: Tang Jie 0005) — George Mason University, Fairfax, VA, USA (and 1 more)
- Jie Tang 0006 — Nanjing University, Nanjing, China
- Jie Tang 0007 — Nanjing University of Information Science and Technology, School of Management Science and Engineering, China (and 1 more)
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2020 – today
- 2022
[c259]Xiao Liu, Kaixuan Ji, Yicheng Fu, Weng Tam, Zhengxiao Du, Zhilin Yang, Jie Tang:
P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks. ACL (2) 2022: 61-68- [c258]Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, Jie Tang:
GLM: General Language Model Pretraining with Autoregressive Blank Infilling. ACL (1) 2022: 320-335 - [c257]Chenguang Wang, Xiao Liu, Zui Chen, Haoyun Hong, Jie Tang, Dawn Song:
DeepStruct: Pretraining of Language Models for Structure Prediction. ACL (Findings) 2022: 803-823 - [c256]Zixuan Ma, Jiaao He, Jiezhong Qiu, Huanqi Cao, Yuanwei Wang, Zhenbo Sun, Liyan Zheng, Haojie Wang, Shizhi Tang, Tianyu Zheng, Junyang Lin, Guanyu Feng, Zeqiang Huang, Jie Gao, Aohan Zeng, Jianwei Zhang, Runxin Zhong, Tianhui Shi, Sha Liu, Weimin Zheng, Jie Tang, Hongxia Yang, Xin Liu, Jidong Zhai, Wenguang Chen:
BaGuaLu: targeting brain scale pretrained models with over 37 million cores. PPoPP 2022: 192-204 - [c255]Xiao Liu, Haoyun Hong, Xinghao Wang, Zeyi Chen, Evgeny Kharlamov, Yuxiao Dong, Jie Tang:
SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs. WWW 2022: 860-870 - [c254]Zhen Yang, Ming Ding, Bin Xu, Hongxia Yang, Jie Tang:
STAM: A Spatiotemporal Aggregation Method for Graph Neural Network-based Recommendation. WWW 2022: 3217-3228 - [c253]Wenzheng Feng, Yuxiao Dong, Tinglin Huang, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, Jie Tang:
GRAND+: Scalable Graph Random Neural Networks. WWW 2022: 3248-3258 - [i85]Zhiyuan Liu, Yixin Cao, Fuli Feng, Xiang Wang, Xindi Shang, Jie Tang, Kenji Kawaguchi, Tat-Seng Chua:
Training Free Graph Neural Networks for Graph Matching. CoRR abs/2201.05349 (2022) - [i84]Jing Zhang, Xiaokang Zhang, Jifan Yu, Jian Tang, Jie Tang, Cuiping Li, Hong Chen:
Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering. CoRR abs/2202.13296 (2022) - [i83]Xiao Liu, Haoyun Hong, Xinghao Wang, Zeyi Chen, Evgeny Kharlamov, Yuxiao Dong, Jie Tang:
SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs. CoRR abs/2203.01044 (2022) - [i82]Wenzheng Feng, Yuxiao Dong, Tinglin Huang, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, Jie Tang:
GRAND+: Scalable Graph Random Neural Networks. CoRR abs/2203.06389 (2022) - [i81]Ning Ding, Yujia Qin, Guang Yang, Fuchao Wei, Zonghan Yang, Yusheng Su, Shengding Hu, Yulin Chen, Chi-Min Chan, Weize Chen, Jing Yi, Weilin Zhao, Xiaozhi Wang, Zhiyuan Liu, Hai-Tao Zheng, Jianfei Chen, Yang Liu, Jie Tang, Juanzi Li, Maosong Sun:
Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models. CoRR abs/2203.06904 (2022) - [i80]Sha Yuan, Shuai Zhao, Jiahong Leng, Zhao Xue, Hanyu Zhao, Jie Tang:
WuDaoMM: A large-scale Multi-Modal Dataset for Pre-training models. CoRR abs/2203.11480 (2022) - [i79]Ming Ding, Wendi Zheng, Wenyi Hong, Jie Tang:
CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers. CoRR abs/2204.14217 (2022) - 2021
- [j95]Zhengyang Song, Jie Tang, Tracy Xiao Liu, Wenjiang Zheng, Lili Wu, Wenzheng Feng, Jing Zhang:
XiaoMu: an AI-driven assistant for MOOCs. Sci. China Inf. Sci. 64(6) (2021) - [j94]Zhen Duan, Xian Sun, Shu Zhao, Jie Chen, Yanping Zhang, Jie Tang:
Hierarchical community structure preserving approach for network embedding. Inf. Sci. 546: 1084-1096 (2021) - [j93]Haodong Zou, Zhen Duan, Xinru Guo, Shu Zhao, Jie Chen, Yanping Zhang, Jie Tang:
On embedding sequence correlations in attributed network for semi-supervised node classification. Inf. Sci. 562: 385-397 (2021) - [j92]Yinyu Jin, Sha Yuan, Zhou Shao, Wendy Hall, Jie Tang:
Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact. Scientometrics 126(3): 2329-2348 (2021) - [j91]Wendy Hall, Noshir Contractor, Jie Tang:
ACM Web Science Conference 2021: conference report. SIGWEB Newsl. 2021(Autumn): 1:1-1:4 (2021) - [j90]Fuli Feng, Xiangnan He, Jie Tang, Tat-Seng Chua:
Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure. IEEE Trans. Knowl. Data Eng. 33(6): 2493-2504 (2021) - [j89]Zhengxiao Du, Jie Tang, Yuhui Ding:
POLAR++: Active One-Shot Personalized Article Recommendation. IEEE Trans. Knowl. Data Eng. 33(6): 2709-2722 (2021) - [c252]Jifan Yu, Yuquan Wang, Qingyang Zhong, Gan Luo, Yiming Mao, Kai Sun, Wenzheng Feng, Wei Xu, Shulin Cao, Kaisheng Zeng, Zijun Yao, Lei Hou, Yankai Lin, Peng Li, Jie Zhou, Bin Xu, Juanzi Li, Jie Tang, Maosong Sun:
MOOCCubeX: A Large Knowledge-centered Repository for Adaptive Learning in MOOCs. CIKM 2021: 4643-4652 - [c251]Chenguang Wang, Xiao Liu, Zui Chen, Haoyun Hong, Jie Tang, Dawn Song:
Zero-Shot Information Extraction as a Unified Text-to-Triple Translation. EMNLP (1) 2021: 1225-1238 - [c250]Yuxuan Shi, Gong Cheng, Trung-Kien Tran, Jie Tang, Evgeny Kharlamov:
Keyword-Based Knowledge Graph Exploration Based on Quadratic Group Steiner Trees. IJCAI 2021: 1555-1562 - [c249]Tinglin Huang, Yuxiao Dong, Ming Ding, Zhen Yang, Wenzheng Feng, Xinyu Wang, Jie Tang:
MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems. KDD 2021: 665-674 - [c248]Qingsong Lv, Ming Ding, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Siming He, Chang Zhou, Jianguo Jiang, Yuxiao Dong, Jie Tang:
Are we really making much progress?: Revisiting, benchmarking and refining heterogeneous graph neural networks. KDD 2021: 1150-1160 - [c247]Xu Zou, Da Yin, Qingyang Zhong, Hongxia Yang, Zhilin Yang, Jie Tang:
Controllable Generation from Pre-trained Language Models via Inverse Prompting. KDD 2021: 2450-2460 - [c246]Xu Zou, Qinkai Zheng, Yuxiao Dong, Xinyu Guan, Evgeny Kharlamov, Jialiang Lu, Jie Tang:
TDGIA: Effective Injection Attacks on Graph Neural Networks. KDD 2021: 2461-2471 - [c245]Junyang Lin, Rui Men, An Yang, Chang Zhou, Yichang Zhang, Peng Wang, Jingren Zhou, Jie Tang, Hongxia Yang:
M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining. KDD 2021: 3251-3261 - [c244]Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu:
Graph Representation Learning: Foundations, Methods, Applications and Systems. KDD 2021: 4044-4045 - [c243]Ming Ding, Yuxiao Dong, Xiao Liu, Jiezhong Qiu, Jie Tang, Zhilin Yang:
The International Workshop on Pretraining: Algorithms, Architectures, and Applications ([email protected] 2021). KDD 2021: 4119-4120 - [c242]Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, Jie Tang:
CogView: Mastering Text-to-Image Generation via Transformers. NeurIPS 2021: 19822-19835 - [c241]Jialin Zhao, Yuxiao Dong, Ming Ding, Evgeny Kharlamov, Jie Tang:
Adaptive Diffusion in Graph Neural Networks. NeurIPS 2021: 23321-23333 - [c240]Yi Ma, Xiaotian Hao, Jianye Hao, Jiawen Lu, Xing Liu, Xialiang Tong, Mingxuan Yuan, Zhigang Li, Jie Tang, Zhaopeng Meng:
A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems. NeurIPS 2021: 23609-23620 - [c239]Zhu Zhang, Jianxin Ma, Chang Zhou, Rui Men, Zhikang Li, Ming Ding, Jie Tang, Jingren Zhou, Hongxia Yang:
UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis. NeurIPS 2021: 27196-27208 - [c238]Qinkai Zheng, Xu Zou, Yuxiao Dong, Yukuo Cen, Da Yin, Jiarong Xu, Yang Yang, Jie Tang:
Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning. NeurIPS Datasets and Benchmarks 2021 - [c237]Jiezhong Qiu, Laxman Dhulipala, Jie Tang, Richard Peng, Chi Wang:
LightNE: A Lightweight Graph Processing System for Network Embedding. SIGMOD Conference 2021: 2281-2289 - [c236]Yuquan Wang, Yanpeng Wang, Yiming Mao, Jifan Yu, Kaisheng Zeng, Lei Hou, Juanzi Li, Jie Tang:
Expertise-Aware Crowdsourcing Taxonomy Enrichment. WISE (1) 2021: 14-29 - [e18]Clare Hooper, Matthew Weber, Katrin Weller, Wendy Hall, Noshir Contractor, Jie Tang:
WebSci '21: 13th ACM Web Science Conference 2021, Virtual Event, United Kingdom, June 21-25, 2021. ACM 2021, ISBN 978-1-4503-8330-1 [contents] - [e17]Jure Leskovec, Marko Grobelnik, Marc Najork, Jie Tang, Leila Zia:
WWW '21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021. ACM / IW3C2 2021, ISBN 978-1-4503-8312-7 [contents] - [e16]Jure Leskovec, Marko Grobelnik, Marc Najork, Jie Tang, Leila Zia:
Companion of The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021. ACM / IW3C2 2021, ISBN 978-1-4503-8313-4 [contents] - [i78]Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang:
M6: A Chinese Multimodal Pretrainer. CoRR abs/2103.00823 (2021) - [i77]Yukuo Cen, Zhenyu Hou, Yan Wang, Qibin Chen, Yizhen Luo, Xingcheng Yao, Aohan Zeng, Shiguang Guo, Peng Zhang, Guohao Dai, Yu Wang, Chang Zhou, Hongxia Yang, Jie Tang:
CogDL: An Extensive Toolkit for Deep Learning on Graphs. CoRR abs/2103.00959 (2021) - [i76]Xiao Liu, Da Yin, Xingjian Zhang, Kai Su, Kan Wu, Hongxia Yang, Jie Tang:
OAG-BERT: Pre-train Heterogeneous Entity-augmented Academic Language Models. CoRR abs/2103.02410 (2021) - [i75]Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang, Xiao Liu, Ruobing Xie, Kai Zhuang, Xu Zhang, Leyu Lin, Philip S. Yu:
Understanding WeChat User Preferences and "Wow" Diffusion. CoRR abs/2103.02930 (2021) - [i74]Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, Jie Tang:
All NLP Tasks Are Generation Tasks: A General Pretraining Framework. CoRR abs/2103.10360 (2021) - [i73]Xiao Liu, Yanan Zheng, Zhengxiao Du, Ming Ding, Yujie Qian, Zhilin Yang, Jie Tang:
GPT Understands, Too. CoRR abs/2103.10385 (2021) - [i72]Xu Zou, Da Yin, Qingyang Zhong, Hongxia Yang, Zhilin Yang, Jie Tang:
Controllable Generation from Pre-trained Language Models via Inverse Prompting. CoRR abs/2103.10685 (2021) - [i71]Jiaao He, Jiezhong Qiu, Aohan Zeng, Zhilin Yang, Jidong Zhai, Jie Tang:
FastMoE: A Fast Mixture-of-Expert Training System. CoRR abs/2103.13262 (2021) - [i70]Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, Jie Tang:
CogView: Mastering Text-to-Image Generation via Transformers. CoRR abs/2105.13290 (2021) - [i69]Zhu Zhang, Jianxin Ma, Chang Zhou, Rui Men, Zhikang Li, Ming Ding, Jie Tang, Jingren Zhou, Hongxia Yang:
UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis. CoRR abs/2105.14211 (2021) - [i68]Xu Zou, Qinkai Zheng, Yuxiao Dong, Xinyu Guan, Evgeny Kharlamov, Jialiang Lu, Jie Tang:
TDGIA: Effective Injection Attacks on Graph Neural Networks. CoRR abs/2106.06663 (2021) - [i67]Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Liang Zhang, Wentao Han, Minlie Huang, Qin Jin, Yanyan Lan, Yang Liu, Zhiyuan Liu, Zhiwu Lu, Xipeng Qiu, Ruihua Song, Jie Tang, Ji-Rong Wen, Jinhui Yuan, Wayne Xin Zhao, Jun Zhu:
Pre-Trained Models: Past, Present and Future. CoRR abs/2106.07139 (2021) - [i66]Xiao Liu, Haoyun Hong, Xinghao Wang, Zeyi Chen, Evgeny Kharlamov, Yuxiao Dong, Jie Tang:
A Self-supervised Method for Entity Alignment. CoRR abs/2106.09395 (2021) - [i65]Yinyu Jin, Sha Yuan, Zhou Shao, Wendy Hall, Jie Tang:
Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact. CoRR abs/2106.11534 (2021) - [i64]Jing Zhou, Yanan Zheng, Jie Tang, Jian Li, Zhilin Yang:
FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning. CoRR abs/2108.06332 (2021) - [i63]Yijia Xiao, Jiezhong Qiu, Ziang Li, Chang-Yu Hsieh, Jie Tang:
Modeling Protein Using Large-scale Pretrain Language Model. CoRR abs/2108.07435 (2021) - [i62]Bo Chen, Jing Zhang, Xiaokang Zhang, Yuxiao Dong, Jian Song, Peng Zhang, Kaibo Xu, Evgeny Kharlamov, Jie Tang:
GCCAD: Graph Contrastive Coding for Anomaly Detection. CoRR abs/2108.07516 (2021) - [i61]Chenguang Wang, Xiao Liu, Zui Chen, Haoyun Hong, Jie Tang, Dawn Song:
Zero-Shot Information Extraction as a Unified Text-to-Triple Translation. CoRR abs/2109.11171 (2021) - [i60]Yanan Zheng, Jing Zhou, Yujie Qian, Ming Ding, Jian Li, Ruslan Salakhutdinov, Jie Tang, Sebastian Ruder, Zhilin Yang:
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding. CoRR abs/2109.12742 (2021) - [i59]Xiao Liu, Kaixuan Ji, Yicheng Fu, Zhengxiao Du, Zhilin Yang, Jie Tang:
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks. CoRR abs/2110.07602 (2021) - [i58]Qinkai Zheng, Xu Zou, Yuxiao Dong, Yukuo Cen, Da Yin, Jiarong Xu, Yang Yang, Jie Tang:
Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning. CoRR abs/2111.04314 (2021) - [i57]Xueyi Liu, Jie Tang:
Network representation learning: A macro and micro view. CoRR abs/2111.10772 (2021) - [i56]Chenhui Zhang, Yufei He, Yukuo Cen, Zhenyu Hou, Jie Tang:
Improving the Training of Graph Neural Networks with Consistency Regularization. CoRR abs/2112.04319 (2021) - [i55]Qingsong Lv, Ming Ding, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Siming He, Chang Zhou, Jianguo Jiang, Yuxiao Dong, Jie Tang:
Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networks. CoRR abs/2112.14936 (2021) - [i54]Tiansi Dong, Achim Rettinger, Jie Tang, Barbara Tversky, Frank van Harmelen:
Structure and Learning (Dagstuhl Seminar 21362). Dagstuhl Reports 11(8): 11-34 (2021) - 2020
- [j88]Jie Tang:
AI OPEN inaugural editorial. AI Open 1: 1 (2020) - [j87]Sha Yuan, Yu Zhang, Jie Tang, Wendy Hall, Juan Bautista Cabotà:
Expert finding in community question answering: a review. Artif. Intell. Rev. 53(2): 843-874 (2020) - [j86]Sha Yuan, Zhou Shao, Xingxing Wei, Jie Tang, Wendy Hall, Yongli Wang, Ying Wang, Ye Wang:
Science behind AI: the evolution of trend, mobility, and collaboration. Scientometrics 124(2): 993-1013 (2020) - [j85]Jie Chen, Jialin Chen, Shu Zhao, Yanping Zhang, Jie Tang:
Exploiting word embedding for heterogeneous topic model towards patent recommendation. Scientometrics 125(3): 2091-2108 (2020) - [j84]Jie Tang:
Message from the Incoming Editor-in-Chief. IEEE Trans. Big Data 6(1): 2 (2020) - [j83]Yuan Yuan, Xuyun Zhang, Jie Tang:
Guest Editorial Special Issue on Privacy and Security in Computational Intelligence. IEEE Trans. Emerg. Top. Comput. Intell. 4(5): 590-592 (2020) - [j82]Si Zhang, Hanghang Tong, Jie Tang, Jiejun Xu, Wei Fan:
Incomplete Network Alignment: Problem Definitions and Fast Solutions. ACM Trans. Knowl. Discov. Data 14(4): 38:1-38:26 (2020) - [j81]Yukuo Cen, Jing Zhang, Gaofei Wang, Yujie Qian, Chuizheng Meng, Zonghong Dai, Hongxia Yang, Jie Tang:
Trust Relationship Prediction in Alibaba E-Commerce Platform. IEEE Trans. Knowl. Data Eng. 32(5): 1024-1035 (2020) - [j80]Dong Zhang, Shu Zhao, Zhen Duan, Jie Chen, Yanping Zhang, Jie Tang:
A Multi-Label Classification Method Using a Hierarchical and Transparent Representation for Paper-Reviewer Recommendation. ACM Trans. Inf. Syst. 38(1): 5:1-5:20 (2020) - [c235]Jifan Yu, Gan Luo, Tong Xiao, Qingyang Zhong, Yuquan Wang, Wenzheng Feng, Junyi Luo, Chenyu Wang, Lei Hou, Juanzi Li, Zhiyuan Liu, Jie Tang:
MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs. ACL 2020: 3135-3142 - [c234]Jiezhong Qiu, Hao Ma, Omer Levy, Wen-tau Yih, Sinong Wang, Jie Tang:
Blockwise Self-Attention for Long Document Understanding. EMNLP (Findings) 2020: 2555-2565 - [c233]Yuxiao Dong, Ziniu Hu, Kuansan Wang, Yizhou Sun, Jie Tang:
Heterogeneous Network Representation Learning. IJCAI 2020: 4861-4867 - [c232]Jifan Yu, Chenyu Wang, Gan Luo, Lei Hou, Juanzi Li, Jie Tang, Minlie Huang, Zhiyuan Liu:
ExpanRL: Hierarchical Reinforcement Learning for Course Concept Expansion in MOOCs. AACL/IJCNLP 2020: 770-780 - [c231]Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, Jie Tang:
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training. KDD 2020: 1150-1160 - [c230]Zhen Yang, Ming Ding, Chang Zhou, Hongxia Yang, Jingren Zhou, Jie Tang:
Understanding Negative Sampling in Graph Representation Learning. KDD 2020: 1666-1676 - [c229]Yukuo Cen, Jianwei Zhang, Xu Zou, Chang Zhou, Hongxia Yang, Jie Tang:
Controllable Multi-Interest Framework for Recommendation. KDD 2020: 2942-2951 - [c228]Ming Ding, Chang Zhou, Hongxia Yang, Jie Tang:
CogLTX: Applying BERT to Long Texts. NeurIPS 2020 - [c227]Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Evgeny Kharlamov, Jie Tang:
Graph Random Neural Networks for Semi-Supervised Learning on Graphs. NeurIPS 2020 - [c226]Jiezhong Qiu, Chi Wang, Ben Liao, Richard Peng, Jie Tang:
A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices. NeurIPS 2020 - [c225]Jibing Gong, Shen Wang, Jinlong Wang, Wenzheng Feng, Hao Peng, Jie Tang, Philip S. Yu:
Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. SIGIR 2020: 79-88 - [c224]Sha Yuan, Zhou Shao, Yangxiao Liang, Jie Tang, Wendy Hall, Gang Liu, Yutian Zhang:
International Scientific Collaboration in Artificial Intelligence An Analysis based on Web Data. WebSci 2020: 69-75 - [c223]Zhou Shao, Zhenting Shen, Sha Yuan, Jie Tang, Yongli Wang, Lili Wu, Wenjiang Zheng:
AI 2000: A Decade of Artificial Intelligence. WebSci 2020: 345-354 - [i53]Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang:
Modelling High-Order Social Relations for Item Recommendation. CoRR abs/2003.10149 (2020) - [i52]Yukuo Cen, Jianwei Zhang, Xu Zou, Chang Zhou, Hongxia Yang, Jie Tang:
Controllable Multi-Interest Framework for Recommendation. CoRR abs/2005.09347 (2020) - [i51]Zhen Yang, Ming Ding, Chang Zhou, Hongxia Yang, Jingren Zhou, Jie Tang:
Understanding Negative Sampling in Graph Representation Learning. CoRR abs/2005.09863 (2020) - [i50]Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Jie Tang:
Graph Random Neural Network. CoRR abs/2005.11079 (2020) - [i49]Sha Yuan, Zhou Shao, Yu Zhang, Xingxing Wei, Tong Xiao, Yifan Wang, Jie Tang:
Attention: to Better Stand on the Shoulders of Giants. CoRR abs/2005.14256 (2020) - [i48]Xiao Liu, Fanjin Zhang, Zhenyu Hou, Zhaoyu Wang, Li Mian, Jing Zhang, Jie Tang:
Self-supervised Learning: Generative or Contrastive. CoRR abs/2006.08218 (2020) - [i47]Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, Jie Tang:
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training. CoRR abs/2006.09963 (2020) - [i46]Shen Wang, Jibing Gong, Jinlong Wang, Wenzheng Feng, Hao Peng, Jie Tang, Philip S. Yu:
Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. CoRR abs/2006.13257 (2020) - [i45]Zhuoyue Xiao, Yutao Zhang, Bo Chen, Xiaozhao Liu, Jie Tang:
A framework for constructing a huge name disambiguation dataset: algorithms, visualization and human collaboration. CoRR abs/2007.02086 (2020) - [i44]Jiezhong Qiu, Chi Wang, Ben Liao, Richard Peng, Jie Tang:
Concentration Bounds for Co-occurrence Matrices of Markov Chains. CoRR abs/2008.02464 (2020) - [i43]Zhengyan Zhang, Xu Han, Hao Zhou, Pei Ke, Yuxian Gu, Deming Ye, Yujia Qin, YuSheng Su, Haozhe Ji, Jian Guan, Fanchao Qi, Xiaozhi Wang, Yanan Zheng, Guoyang Zeng, Huanqi Cao, Shengqi Chen, Daixuan Li, Zhenbo Sun, Zhiyuan Liu, Minlie Huang, Wentao Han, Jie Tang, Juanzi Li, Xiaoyan Zhu, Maosong Sun:
CPM: A Large-scale Generative Chinese Pre-trained Language Model. CoRR abs/2012.00413 (2020) - [i42]Bo Chen, Jing Zhang, Xiaokang Zhang, Xiaobin Tang, Lingfan Cai, Hong Chen, Cuiping Li, Peng Zhang, Jie Tang:
COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking. CoRR abs/2012.11336 (2020)
2010 – 2019
- 2019
- [j79]Huaiyu Wan, Yutao Zhang, Jing Zhang, Jie Tang:
AMiner: Search and Mining of Academic Social Networks. Data Intell. 1(1): 58-76 (2019) - [j78]Daifeng Li, Yintian Wang, Andrew Madden, Ying Ding, Jie Tang, Gordon Guo-Zheng Sun, Ning Zhang, Enguo Zhou:
Analyzing stock market trends using social media user moods and social influence. J. Assoc. Inf. Sci. Technol. 70(9): 1000-1013 (2019) - [j77]Christos Giatsidis, Giannis Nikolentzos, Chenhui Zhang, Jie Tang, Michalis Vazirgiannis:
Rooted citation graphs density metrics for research papers influence evaluation. J. Informetrics 13(2): 757-768 (2019) - [c222]Wenzheng Feng, Jie Tang, Tracy Xiao Liu:
Understanding Dropouts in MOOCs. AAAI 2019: 517-524 - [c221]Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, Jie Tang:
Cognitive Graph for Multi-Hop Reading Comprehension at Scale. ACL (1) 2019: 2694-2703 - [c220]Jifan Yu, Chenyu Wang, Gan Luo, Lei Hou, Juanzi Li, Zhiyuan Liu, Jie Tang:
Course Concept Expansion in MOOCs with External Knowledge and Interactive Game. ACL (1) 2019: 4292-4302 - [c219]George Panagopoulos, Christos Xypolopoulos, Konstantinos Skianis, Christos Giatsidis, Jie Tang, Michalis Vazirgiannis:
Scientometrics for Success and Influence in the Microsoft Academic Graph. COMPLEX NETWORKS (2) 2019: 1007-1017 - [c218]Jie Zhang, Yan Wang, Jie Tang:
A Fast Network Embedding Approach with Preserving Hierarchical Proximities. DSC 2019: 142-149 - [c217]Tianqi Wang, Qi Li, Jing Gao, Xia Jing, Jie Tang:
Improving Peer Assessment Accuracy by Incorporating Relative Peer Grades. EDM 2019 - [c216]Qibin Chen, Junyang Lin, Yichang Zhang, Ming Ding, Yukuo Cen, Hongxia Yang, Jie Tang:
Towards Knowledge-Based Recommender Dialog System. EMNLP/IJCNLP (1) 2019: 1803-1813 - [c215]Yu Han, Jie Tang, Qian Chen:
Network Embedding under Partial Monitoring for Evolving Networks. IJCAI 2019: 2463-2469 - [c214]