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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
- 2023
[j114]Huan-jing Zhao, Pinde Rui, Jie Chen, Yanping Zhang, Yi Wang, Shu Zhao, Jie Tang:
HINChip: Heterogeneous Information Network Representation with Community Hierarchy Preserving. Knowl. Based Syst. 264: 110343 (2023)- [j113]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:
Parameter-efficient fine-tuning of large-scale pre-trained language models. Nat. Mac. Intell. 5(3): 220-235 (2023) - [j112]Da Yin, Weng Lam Tam, Ming Ding, Jie Tang:
MRT: Tracing the Evolution of Scientific Publications. IEEE Trans. Knowl. Data Eng. 35(1): 711-724 (2023) - [j111]Xiao Liu, Fanjin Zhang, Zhenyu Hou, Li Mian, Zhaoyu Wang, Jing Zhang, Jie Tang:
Self-Supervised Learning: Generative or Contrastive. IEEE Trans. Knowl. Data Eng. 35(1): 857-876 (2023) - [j110]Zhengxiao Du, Chang Zhou, Jiangchao Yao, Teng Tu, Letian Cheng, Hongxia Yang, Jingren Zhou, Jie Tang:
CogKR: Cognitive Graph for Multi-Hop Knowledge Reasoning. IEEE Trans. Knowl. Data Eng. 35(2): 1283-1295 (2023) - [j109]Xiao Liu, Li Mian, Yuxiao Dong, Fanjin Zhang, Jing Zhang, Jie Tang, Peng Zhang, Jibing Gong, Kuansan Wang:
OAG$_{\mathrm {know}}$ know : Self-Supervised Learning for Linking Knowledge Graphs. IEEE Trans. Knowl. Data Eng. 35(2): 1895-1908 (2023) - [j108]Zhenyu Hou, Yukuo Cen, Yuxiao Dong, Jie Zhang, Jie Tang:
Automated Unsupervised Graph Representation Learning. IEEE Trans. Knowl. Data Eng. 35(3): 2285-2298 (2023) - [j107]Shu Zhao, Ziwei Du, Jie Chen, Yanping Zhang, Jie Tang, Philip S. Yu:
Hierarchical Representation Learning for Attributed Networks. IEEE Trans. Knowl. Data Eng. 35(3): 2641-2656 (2023) - [j106]Zhen Yang, Ming Ding, Xu Zou, Jie Tang, Bin Xu, Chang Zhou, Hongxia Yang:
Region or Global? A Principle for Negative Sampling in Graph-Based Recommendation. IEEE Trans. Knowl. Data Eng. 35(6): 6264-6277 (2023) - [c278]Zhenyu Hou, Yufei He, Yukuo Cen, Xiao Liu, Yuxiao Dong, Evgeny Kharlamov, Jie Tang:
GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner. WWW 2023: 737-746 - [c277]Yukuo Cen, Zhenyu Hou, Yan Wang, Qibin Chen, Yizhen Luo, Zhongming Yu, Hengrui Zhang, Xingcheng Yao, Aohan Zeng, Shiguang Guo, Yuxiao Dong, Yang Yang, Peng Zhang, Guohao Dai, Yu Wang, Chang Zhou, Hongxia Yang, Jie Tang:
CogDL: A Comprehensive Library for Graph Deep Learning. WWW 2023: 747-758 - [c276]Dan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov, Jie Tang:
ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation. WWW 2023: 759-769 - [e20]Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos Castillo, Geert-Jan Houben:
Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023. ACM 2023, ISBN 978-1-4503-9416-1 [contents] - [e19]Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos Castillo, Geert-Jan Houben:
Companion Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023. ACM 2023, ISBN 978-1-4503-9419-2 [contents] - [i103]Yuyang Xie, Jiezhong Qiu, Laxman Dhulipala, Wenjian Yu, Jie Tang, Richard Peng, Chi Wang:
Towards Lightweight and Automated Representation Learning System for Networks. CoRR abs/2302.07084 (2023) - [i102]Bo Chen, Jing Zhang, Fanjin Zhang, Tianyi Han, Yuqing Cheng, Xiaoyan Li, Yuxiao Dong, Jie Tang:
Web-Scale Academic Name Disambiguation: the WhoIsWho Benchmark, Leaderboard, and Toolkit. CoRR abs/2302.11848 (2023) - [i101]Ji Qi, Jifan Yu, Teng Tu, Kunyu Gao, Yifan Xu, Xinyu Guan, Xiaozhi Wang, Yuxiao Dong, Bin Xu, Lei Hou, Juanzi Li, Jie Tang, Weidong Guo, Hui Liu, Yu Xu:
GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation. CoRR abs/2303.14655 (2023) - [i100]Qinkai Zheng, Xiao Xia, Xu Zou, Yuxiao Dong, Shan Wang, Yufei Xue, Zihan Wang, Lei Shen, Andi Wang, Yang Li, Teng Su, Zhilin Yang, Jie Tang:
CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Evaluations on HumanEval-X. CoRR abs/2303.17568 (2023) - [i99]Zhenyu Hou, Yufei He, Yukuo Cen, Xiao Liu, Yuxiao Dong, Evgeny Kharlamov, Jie Tang:
GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner. CoRR abs/2304.04779 (2023) - [i98]Jiazheng Xu, Xiao Liu, Yuchen Wu, Yuxuan Tong, Qinkai Li, Ming Ding, Jie Tang, Yuxiao Dong:
ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation. CoRR abs/2304.05977 (2023) - 2022
- [j105]Shu Zhao, Jialin Chen, Jie Chen, Yanping Zhang, Jie Tang:
Hierarchical label with imbalance and attributed network structure fusion for network embedding. AI Open 3: 91-100 (2022) - [j104]Jie Tang, Song-Ya Ma, Qi Li:
Probabilistic Hierarchical Quantum Information Splitting of Arbitrary Multi-Qubit States. Entropy 24(8): 1077 (2022) - [j103]Bo Chen, Jing Zhang, Jie Tang, Lingfan Cai, Zhaoyu Wang, Shu Zhao, Hong Chen, Cuiping Li:
CONNA: Addressing Name Disambiguation on the Fly. IEEE Trans. Knowl. Data Eng. 34(7): 3139-3152 (2022) - [j102]Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang:
Modelling High-Order Social Relations for Item Recommendation. IEEE Trans. Knowl. Data Eng. 34(9): 4385-4397 (2022) - [j101]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. IEEE Trans. Knowl. Data Eng. 34(12): 6033-6046 (2022) - [c275]Bo Chen, Jing Zhang, Xiaokang Zhang, Xiaobin Tang, Lingfan Cai, Hong Chen, Cuiping Li, Peng Zhang, Jie Tang:
CODE: Contrastive Pre-training with Adversarial Fine-Tuning for Zero-Shot Expert Linking. AAAI 2022: 11846-11854 - [c274]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 - [c273]Daniel Zhang-li, Jing Zhang, Jifan Yu, Xiaokang Zhang, Peng Zhang, Jie Tang, Juanzi Li:
HOSMEL: A Hot-Swappable Modularized Entity Linking Toolkit for Chinese. ACL (demo) 2022: 214-223 - [c272]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 - [c271]Yanan Zheng, Jing Zhou, Yujie Qian, Ming Ding, Chonghua Liao, Li Jian, Ruslan Salakhutdinov, Jie Tang, Sebastian Ruder, Zhilin Yang:
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding. ACL (1) 2022: 501-516 - [c270]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 - [c269]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. ACL (1) 2022: 5773-5784 - [c268]Jing Zhou, Yanan Zheng, Jie Tang, Li Jian, Zhilin Yang:
FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning. ACL (1) 2022: 8646-8665 - [c267]Zhuoyi Yang, Ming Ding, Yanhui Guo, Qingsong Lv, Jie Tang:
Parameter-Efficient Tuning Makes a Good Classification Head. EMNLP 2022: 7576-7586 - [c266]Shu Zhao, Ziwei Du, Jie Chen, Yanping Zhang, Jie Tang, Philip S. Yu:
Hierarchical Representation Learning for Attributed Networks. ICDE 2022: 1497-1498 - [c265]Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael W. Mahoney, Alvin Cheung:
GACT: Activation Compressed Training for Generic Network Architectures. ICML 2022: 14139-14152 - [c264]Ziang Li, Ming Ding, Weikai Li, Zihan Wang, Ziyu Zeng, Yukuo Cen, Jie Tang:
Rethinking the Setting of Semi-supervised Learning on Graphs. IJCAI 2022: 3243-3249 - [c263]Zhenyu Hou, Xiao Liu, Yukuo Cen, Yuxiao Dong, Hongxia Yang, Chunjie Wang, Jie Tang:
GraphMAE: Self-Supervised Masked Graph Autoencoders. KDD 2022: 594-604 - [c262]Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, Jie Tang:
Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries. KDD 2022: 1120-1130 - [c261]Xiao Liu, Da Yin, Jingnan Zheng, Xingjian Zhang, Peng Zhang, Hongxia Yang, Yuxiao Dong, Jie Tang:
OAG-BERT: Towards a Unified Backbone Language Model for Academic Knowledge Services. KDD 2022: 3418-3428 - [c260]Jifan Yu, Xiaohan Zhang, Yifan Xu, Xuanyu Lei, Xinyu Guan, Jing Zhang, Lei Hou, Juanzi Li, Jie Tang:
XDAI: A Tuning-free Framework for Exploiting Pre-trained Language Models in Knowledge Grounded Dialogue Generation. KDD 2022: 4422-4432 - [c259]Ming Ding, Wendi Zheng, Wenyi Hong, Jie Tang:
CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers. NeurIPS 2022 - [c258]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 - [c257]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 - [c256]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 - [c255]Wenzheng Feng, Yuxiao Dong, Tinglin Huang, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, Jie Tang:
GRAND+: Scalable Graph Random Neural Networks. WWW 2022: 3248-3258 - [i97]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) - [i96]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) - [i95]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) - [i94]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) - [i93]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) - [i92]Jibing Gong, Yao Wan, Ye Liu, Xuewen Li, Yi Zhao, Cheng Wang, Qing Li, Wenzheng Feng, Jie Tang:
Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks. CoRR abs/2203.11011 (2022) - [i91]Ming Ding, Wendi Zheng, Wenyi Hong, Jie Tang:
CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers. CoRR abs/2204.14217 (2022) - [i90]Chenguang Wang, Xiao Liu, Zui Chen, Haoyun Hong, Jie Tang, Dawn Song:
DeepStruct: Pretraining of Language Models for Structure Prediction. CoRR abs/2205.10475 (2022) - [i89]Zhenyu Hou, Xiao Liu, Yukuo Cen, Yuxiao Dong, Hongxia Yang, Chunjie Wang, Jie Tang:
GraphMAE: Self-Supervised Masked Graph Autoencoders. CoRR abs/2205.10803 (2022) - [i88]Ziang Li, Ming Ding, Weikai Li, Zihan Wang, Ziyu Zeng, Yukuo Cen, Jie Tang:
Rethinking the Setting of Semi-supervised Learning on Graphs. CoRR abs/2205.14403 (2022) - [i87]Wenyi Hong, Ming Ding, Wendi Zheng, Xinghan Liu, Jie Tang:
CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers. CoRR abs/2205.15868 (2022) - [i86]Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael W. Mahoney, Alvin Cheung:
GACT: Activation Compressed Training for General Architectures. CoRR abs/2206.11357 (2022) - [i85]Weng Lam Tam, Xiao Liu, Kaixuan Ji, Lilong Xue, Xingjian Zhang, Yuxiao Dong, Jiahua Liu, Maodi Hu, Jie Tang:
Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated Neural Text Retrievers. CoRR abs/2207.07087 (2022) - [i84]Qingyang Zhong, Jifan Yu, Zheyuan Zhang, Yiming Mao, Yuquan Wang, Yankai Lin, Lei Hou, Juanzi Li, Jie Tang:
Towards a General Pre-training Framework for Adaptive Learning in MOOCs. CoRR abs/2208.04708 (2022) - [i83]Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, Jie Tang:
Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries. CoRR abs/2208.07638 (2022) - [i82]Aohan Zeng, Xiao Liu, Zhengxiao Du, Zihan Wang, Hanyu Lai, Ming Ding, Zhuoyi Yang, Yifan Xu, Wendi Zheng, Xiao Xia, Weng Lam Tam, Zixuan Ma, Yufei Xue, Jidong Zhai, Wenguang Chen, Peng Zhang, Yuxiao Dong, Jie Tang:
GLM-130B: An Open Bilingual Pre-trained Model. CoRR abs/2210.02414 (2022) - [i81]Zhuoyi Yang, Ming Ding, Yanhui Guo, Qingsong Lv, Jie Tang:
Parameter-Efficient Tuning Makes a Good Classification Head. CoRR abs/2210.16771 (2022) - 2021
- [j100]Xueyi Liu, Jie Tang:
Network representation learning: A macro and micro view. AI Open 2: 43-64 (2021) - [j99]Sha Yuan, Hanyu Zhao, Zhengxiao Du, Ming Ding, Xiao Liu, Yukuo Cen, Xu Zou, Zhilin Yang, Jie Tang:
WuDaoCorpora: A super large-scale Chinese corpora for pre-training language models. AI Open 2: 65-68 (2021) - [j98]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. AI Open 2: 93-99 (2021) - [j97]Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Yuan Yao, Ao Zhang, 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. AI Open 2: 225-250 (2021) - [j96]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) - [j95]Zhongying Zhao, Hui Zhou, Chao Li, Jie Tang, Qingtian Zeng:
DeepEmLAN: Deep embedding learning for attributed networks. Inf. Sci. 543: 382-397 (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) - [c254]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 - [c253]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 - [c252]Sisai Fang, Gaojie Chen, Peng Xu, Jie Tang, Jonathon A. Chambers:
SINR Maximization for RIS-Assisted Secure Dual-Function Radar Communication Systems. GLOBECOM 2021: 1-6 - [c251]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 - [c250]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 - [c249]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 - [c248]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 - [c247]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 - [c246]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 - [c245]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 - [c244]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 - [c243]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 - [c242]Jialin Zhao, Yuxiao Dong, Ming Ding, Evgeny Kharlamov, Jie Tang:
Adaptive Diffusion in Graph Neural Networks. NeurIPS 2021: 23321-23333 - [c241]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 - [c240]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 - [c239]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 - [c238]Jiezhong Qiu, Laxman Dhulipala, Jie Tang, Richard Peng, Chi Wang:
LightNE: A Lightweight Graph Processing System for Network Embedding. SIGMOD Conference 2021: 2281-2289 - [c237]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] - [i80]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) - [i79]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) - [i78]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) - [i77]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) - [i76]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) - [i75]Xiao Liu, Yanan Zheng, Zhengxiao Du, Ming Ding, Yujie Qian, Zhilin Yang, Jie Tang:
GPT Understands, Too. CoRR abs/2103.10385 (2021) - [i74]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) - [i73]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) - [i72]