Jie Tang (Tang, Jie) 唐 杰

RESEARCH   Go Top
I am recently working on artificial general intelligence, graph neural networks, social network mining, and academic knowledge graph.

Large Pre-trained Models   [ChatGLM: 从千亿模型到ChatGPT (in Chinese)]  [Keynote@AIED'22/NetSci'22: Pre-Training the World (in English)]
	GLM-130B (ICLR'23) is an open bilingual (English & Chinese) bidirectional dense model with 130 billion parameters, pre-trained using the General Language Model (GLM) algorithm (ACL'22). GLM-130B has been trained on over 1 trillion text tokens and exhibits quite a few unique features.     Based on GLM-130B, we have developed ChatGLM by applying techniques such as supervised fine-tune and RLHF. The open-sourced version ChatGLM-6B tops the trending of Huggingface for more than three weeks. Models and codes: [GLM-130B] [ChatGLM-6B] [GLM] [CogView] [CogVideo] [CodeGeex]
Representation Learning on Networks   [GNN&Self-supervised Learning] [人工智能下一个十年]
	The goal is to automatically encode network structure into low-dimensional space (embeddings), using techniques such as neural networks.     We theoretically prove that recent models such as DeepWalk, LINE, PTE, and node2vec can be unified into the matrix factorization framework with closed forms. we present a new method NetMF, which significantly outperforms DeepWalk and LINE for conventional network mining tasks (Qiu et al., WSDM'18). Based on the learned representations, we further propose a multi-head attention network for predicting user behavior (Qiu et al., KDD'18) and NetSMF for large scale networks (Qiu et al., WWW'19). Further, we incorporate user feedback into the prediction and propose a bandit learning model (Qi et al., NeurIPS'18). Datasets and codes: [NetMF]  [DeepInf]
Social Network Mining  [IC2S2'19 Tutorial]  [KDD'18 Tutorial]   [Book]  [Survey]
	Online social networks already become a bridge to connect our physical daily life with the virtual information space, producing huge volume of networked data. We aim to understand the mechanism underlying the dynamics of social interaction between users and information diffusion in the network.    We propose a new method Topical Affinity Propagation (TAP) to model the topic-level social influence (Tang et al., KDD'09), conformity influence analysis (Tang et al., KDD'13), structural influence (Zhang et al., AAAI'17), inferring social tie (Tang et al., WSDM'12, Tang et al., TOIS'16), and user demographics (Dong et al., KDD'14). At the macro-level, we focus on mining top-k structural hole spanners, who control the information diffusion across different communities (Lou and Tang, WWW'13) and following link diffusion (Zhang et al., TKDE'15). Datasets and codes: [Topic-Influence]  [Structural hole] [Datasets for SNA]
Academic Knowledge Graph   [Tutorial]  [System]   [Career Trajectory]
	We focus on building large-scale knowledge graph, particularly for scholarly data. In this research, we work on various topics including Expert Finding ( Qian et al., IJCAI'18; Tang et al., Machine Learning J'18 ) Career Trajectory Mining ( Wu et al., IJCAI'18 ) Social Recommendation (Tang et al., KDD'12), Information/knowledge Integration (Zhong et al., SIGMOD'09, Wang et al., WWW'12, Wang et al., IJCAI'13), Name Disambiguation (Tang et al., TKDE'12, Zhang et al., KDD'18 ) Summarization (Yang et al., SIGIR'11), Content Alignment (Hou et al., IJCAI'13; Hou et al., TOIS'17 ), Similarity Search (Zhang et al., TOIS'17).    Based on these research, we have developed a system AMiner (ArnetMiner) (Tang et al., KDD'08 (SIGKDD Test-of-Time Award); Tang et al., TKDD'10), for academic search and mining. The system has over 136 million researchers and 200 million papers. Since 2006, the system has attracted over 10 million independent IP accesses from more than 220 countries/regions. Datasets and codes: [AMiner Dataset]  [Open Academic Graph]

SELECTED PUBLICATIONS (A COMPLETE LIST)   Go Top

Summary: Research interest: Artificial Intelligence, Social Networks, Data Mining, Knowledge Graph. I have published 400+ articles in major computer science conferences, including IJCAI / AAAI (30+), NIPS/ICML (10+), KDD (40+), and ~100 articles in the core journals of computer science including TKDE/TKDD/TOIS/TAC (40+).

Social Network / Data Mining / Machine Learning

• Zhen Yang, Ming Ding, Tinglin Huang, Yukuo Cen, Junshuai Song, Bin Xu, Yuxiao Dong, and Jie Tang. Does Negative Sampling Matter? A Review with Insights into its Theory and Applications. IEEE Transaction on Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
• Zhengxiao Du, Aohan Zeng, Yuxiao Dong, and Jie Tang. Understanding Emergent Abilities of Language Models from the Loss Perspective. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS'24). [PDF]
• Weihan Wang, Qingsong Lv, Wenmeng Yu, Wenyi Hong, Ji Qi, Yan Wang, Junhui Ji, Zhuoyi Yang, Lei Zhao, XiXuan Song, Jiazheng Xu, Keqin Chen, Bin Xu, Juanzi Li, Yuxiao Dong, Ming Ding, and Jie Tang. CogVLM: Visual Expert for Pretrained Language Models. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS'24). [PDF] [*Code&Data&Model*]
• Xingyi Cheng, Bo Chen, Pan Li, Jing Gong, Jie Tang, and Le Song. Training Compute-Optimal Protein Language Models. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS'24). [PDF] [*Code&Data&Model*]
• Bo Chen, Zhilei Bei, Xingyi Cheng, Pan Li, Jie Tang, and Le Song. MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS'24). [PDF] [*Code&Data&Model*]
• Dan Zhang, Sining Zhoubian, Ziniu Hu, Yisong Yue, Yuxiao Dong, and Jie Tang. ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS'24). [PDF] [*Code&Data&Model*]
• Dan Zhang, Ziniu Hu, Sining Zhoubian, Zhengxiao Du, Kaiyu Yang, Zihan Wang, Yisong Yue, Yuxiao Dong, and Jie Tang. SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (DB Track) (NeurIPS'24). [PDF] [*Code&Data&Model*]
• Bosi Wen, Pei Ke, Xiaotao Gu, Lindong Wu, Hao Huang, Jinfeng Zhou, Wenchuang Li, Binxin Hu, Wendy Gao, Jiaxing Xu, Yiming Liu, Jie Tang, Hongning Wang, and Minlie Huang. Benchmarking Complex Instruction-Following with Multiple Constraints Composition. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (DB Track) (NeurIPS'24). [PDF] [*Code&Data&Model*]
• Zeyao Ma, Bohan Zhang, Jing Zhang, Jifan Yu, Xiaokang Zhang, Xiaohan Zhang, Sijia Luo, Xi Wang, and Jie Tang. SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (DB Track) (NeurIPS'24). [PDF] [*Code&Data&Model*]
• Hanyu Lai, Xiao Liu, Iat Long Iong, Shuntian Yao, Yuxuan Chen, Pengbo Shen, Yu Hao, Hanchen Zhang, Xiaohan Zhang, Yuxiao Dong, and Jie Tang. AutoWebGLM: A Large Language Model-based Web Navigating Agent. In Proceedings of the Thirty ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'24).
• Huanjing Zhao, Beining Yang, Yukuo Cen, Junyu Ren, Chenhui Zhang, Yuxiao Dong, Evgeny Kharlamov, Shu Zhao, and Jie Tang. Pre-Training and Prompting for Few-Shot Node Classification on Text-Attributed Graphs. In Proceedings of the Thirty ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'24).
• Fanjin Zhang, Shi Shijie, Yifan Zhu, Bo Chen, Yukuo Cen, Jifan Yu, Yelin Chen, Lulu Wang, Qingfei Zhao, Yuqing Cheng, Tianyi Han, Yuwei An, Dan Zhang, Weng Lam Tam, Kun Cao, Yunhe Pang, Xinyu Guan, Huihui Yuan, Jian Song, XiaoYan Li, Yuxiao Dong, and Jie Tang. OAG-Bench: A Human-Curated Benchmark for Academic Graph Mining. In Proceedings of the Thirty ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'24).
• Haozhe Ji, Cheng Lu, Yilin Niu, Pei Ke, Hongning Wang, Jun Zhu, Jie Tang, and Minlie Huang. Towards Efficient and Exact Optimization of Language Model Alignment. In Proceedings of the 41st International Conference on Machine Learning (ICML'24).
• Yushi Bai, Xin Lv, Jiajie Zhang, Hongchang Lyu, Jiankai Tang, Zhidian Huang, Zhengxiao Du, Xiao Liu, Aohan Zeng, Lei Hou, Yuxiao Dong, Jie Tang, and Juanzi Li. LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding. In Proceedings of the 62th Annual Meeting of the Association of Computational Linguistics (ACL'24).
• Jiale Cheng, Xiao Liu, Kehan Zheng, Pei Ke, Hongning Wang, Yuxiao Dong, Jie Tang, and Minlie Huang. Black-Box Prompt Optimization: Aligning Large Language Models without Model Training. In Proceedings of the 62th Annual Meeting of the Association of Computational Linguistics (ACL'24).
• Zhexin Zhang, Leqi Lei, Lindong Wu, Rui Sun, Yongkang Huang, Chong Long, Xiao Liu, Xuanyu Lei, Jie Tang, and Minlie Huang. SafetyBench: Evaluating the Safety of Large Language Models. In Proceedings of the 62th Annual Meeting of the Association of Computational Linguistics (ACL'24).
• Xiao Liu, Xuanyu Lei, Shengyuan Wang, Yue Huang, Andrew Zhuoer Feng, Bosi Wen, Jiale Cheng, Pei Ke, Yifan Xu, Weng Lam Tam, Xiaohan Zhang, Lichao Sun, Xiaotao Gu, Hongning Wang, Jing Zhang, Minlie Huang, Yuxiao Dong, and Jie Tang. AlignBench: Benchmarking Chinese Alignment of Large Language Models. In Proceedings of the 62th Annual Meeting of the Association of Computational Linguistics (ACL'24).
• Xiaokang Zhang, Zijun Yao, Jing Zhang, Kaifeng Yun, Jifan Yu, Juanzi Li, and Jie Tang. Transferable and Efficient Non-Factual Content Detection via Probe Training with Offline Consistency Checking. In Proceedings of the 62th Annual Meeting of the Association of Computational Linguistics (ACL'24).
• Pei Ke, Bosi Wen, Andrew Zhuoer Feng, Xiao Liu, Xuanyu Lei, Jiale Cheng, Shengyuan Wang, Aohan Zeng, Yuxiao Dong, Hongning Wang, Jie Tang, and Minlie Huang. CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation. In Proceedings of the 62th Annual Meeting of the Association of Computational Linguistics (ACL'24).
• Aohan Zeng, Mingdao Liu, Rui Lu, Bowen Wang, Xiao Liu, Yuxiao Dong, and Jie Tang. AgentTuning: Enabling Generalized Agent Abilities for LLMs. In Proceedings of the 62th Annual Meeting of the Association of Computational Linguistics (Findings of ACL'24).
• Shudan Zhang, Hanlin Zhao, Xiao Liu, Qinkai Zheng, Zehan Qi, Xiaotao Gu, Yuxiao Dong, and Jie Tang. NaturalCodeBench: A Challenging Application-Driven Dataset for Code Synthesis Evaluation. In Proceedings of the 62th Annual Meeting of the Association of Computational Linguistics (Findings of ACL'24).
• Kejuan Yang, Xiao Liu, Kaiwen Men, Aohan Zeng, Yuxiao Dong, and Jie Tang. Revisiting Parallel Context Windows: A Frustratingly Simple Alternative and Chain-of-Thought Deterioration. In Proceedings of the 62th Annual Meeting of the Association of Computational Linguistics (Findings of ACL'24).
• Wenyi Hong, Weihan Wang, Qingsong Lv, Jiazheng Xu, Wenmeng Yu, Junhui Ji, Yan Wang, Zihan Wang, Yuxiao Dong, Ming Ding, and Jie Tang. CogAgent: A Visual Language Model for GUI Agents. In Proceedings of the 2024 International Conference on Computer Vision and Pattern Recognition (CVPR'24).
• Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, and Jie Tang. AgentBench: Evaluating LLMs as Agents. In Proceedings of the 12th International Conference on Learning Representations (ICLR'24). [PDF] [*Code&Model*] [*@ChatGLM*]
• Jiayan Teng, Wendi Zheng, Ming Ding, Wenyi Hong, Jianqiao Wangni, Zhuoyi Yang, and Jie Tang. Relay Diffusion: Unifying diffusion process across resolutions for image synthesis. In Proceedings of the 12th International Conference on Learning Representations (ICLR'24). [PDF] [*Code&Model*] [*@ChatGLM*]
• Jifan Yu, Xiaozhi Wang, Shangqing Tu, Shulin Cao, Daniel Zhang-Li, Xin Lv, Hao Peng, Zijun Yao, Xiaohan Zhang, Hanming Li, Chunyang Li, Zheyuan Zhang, Yushi Bai, Yantao Liu, Amy Xin, Kaifeng Yun, Linlu GONG, Nianyi Lin, Jianhui Chen, Zhili Wu, Yunjia Qi, Weikai Li, Yong Guan, Kaisheng Zeng, Ji Qi, Hailong Jin, Jinxin Liu, Yu Gu, Yuan Yao, Ning Ding, Lei Hou, Zhiyuan Liu, Xu Bin, Jie Tang, and Juanzi Li. KoLA: Carefully Benchmarking World Knowledge of Large Language Models. In Proceedings of the 12th International Conference on Learning Representations (ICLR'24). [PDF]
• Dan Zhang, Yangliao Geng, Wenwen Gong, Zhongang Qi, Zhiyu Chen, Xing Tang, Ying Shan, Yuxiao Dong, and Jie Tang. RecDCL: Dual Contrastive Learning for Recommendation. In Proceedings of the Web Conference 2024 (WWW'24). [PDF] [*Code&Data*]
• Yuqing Cheng, Bo Chen, Fanjin Zhang, and Jie Tang. BOND: Bootstrapping From-Scratch Name Disambiguation with Multi-task Promoting. In Proceedings of the Web Conference 2024 (WWW'24). [PDF] [*Code&Data*]
• Zhen Yang, Zhou Shao, Yuxiao Dong, and Jie Tang. TriSampler: A Better Negative Sampling Principle for Dense Retrieval. In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24). https://arxiv.org/pdf/2402.11855
• Ming Zhou, Wenzheng Feng, Yifan Zhu, Dan Zhang, Yuxiao Dong, and Jie Tang. Semi-Supervised Social Bot Detection with Initial Residual Relation Attention Networks. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'23). pages 207-224. [PDF] [*Demo*] (Best Student Paper)
• Jiazheng Xu, Xiao Liu, Yuchen Wu, Yuxuan Tong, Qinkai Li, Ming Ding, Jie Tang, and Yuxiao Dong. ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation. In Proceedings of the Thirty-Seventh Annual Conference on Neural Information Processing Systems (NeurIPS'23). [PDF] [*Code&Data&Model*]
• Qinkai Zheng, Xiao Xia, Xu Zou, Yuxiao Dong, Shan Wang, Yufei Xue, Lei Shen, Zihan Wang, Andi Wang, Yang Li, Teng Su, Zhilin Yang, and Jie Tang. CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
• Xiao Liu, Hanyu Lai, Yu Hao, Yifan Xu, Aohan Zeng, Zhengxiao Du, Peng Zhang, Yuxiao Dong, and Jie Tang. WebGLM: Towards An Efficient Web-enhanced Question Answering System with Human Preference. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
• Jing Zhang, Xiaokang Zhang, Daniel Zhang-Li, Jifan Yu, Zijun Yao, Zeyao Ma, Yiqi Xu, Haohua Wang, Xiaohan Zhang, Nianyi Lin, Sunrui Lu, Jie Tang, and Juanzi Li. GLM-Dialog: Noise-tolerant Pre-Training for Knowledge-grounded Dialogue Generation. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
• Zhen Yang, Tinglin Huang, Ming Ding, Yuxiao Dong, Zhitao Ying, Yukuo Cen, Yangliao Geng, and Jie Tang. BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
• Yifan Zhu, Fangpeng Cong, Dan Zhang, Wenwen Gong, Qika Lin, Wenzheng Feng, Yuxiao Dong, and Jie Tang. WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
• Bo Chen, Jing Zhang, Fanjin Zhang, Tianyi Han, Yuqing Cheng, XiaoYan Li, Yuxiao Dong, and Jie Tang. Web-Scale Academic Name Disambiguation: the WhoIsWho Benchmark, Leaderboard, and Toolkit. In Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23). [PDF] [*Code&Data*]
• Yuyang Xie, Yuxiao Dong, Jiezhong Qiu, Wenjian Yu, Xu Feng, and Jie Tang. SketchNE: Embedding Billion-Scale Networks Accurately in One Hour. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2023 (to appear).
• 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, Zhiyuan Liu, Peng Zhang, Yuxiao Dong, and Jie Tang. GLM-130B: An Open Bilingual Pre-trained Model. In Proceedings of the 11th International Conference on Learning Representations (ICLR'23). [PDF] [*Code&Model*] [*Blog*] [*Demo*] [*ChatGLM*]
• Wenyi Hong, Ming Ding, Wendi Zheng, Xinghan Liu, and Jie Tang. CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers. In Proceedings of the 11th International Conference on Learning Representations (ICLR'23). [PDF] [Poster] [*Code&Model*] [*Demo*]
• 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, and Jie Tang. CogDL: A Comprehensive Library for Graph Deep Learning. In Proceedings of the Web Conference 2023 (WWW'23). [PDF] [*Code&Data*]
• Zhenyu Hou, Yufei He, Yukuo Cen, Xiao Liu, Yuxiao Dong, Evgeny Kharlamov, and Jie Tang. GraphMAE2: A Decoding-enhanced Masked Self-supervised Graph Learner. In Proceedings of the Web Conference 2023 (WWW'23) (accepted). [PDF] [*Code&Data*]
• Dan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov, and Jie Tang. ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation. In Proceedings of the Web Conference 2023 (WWW'23) (accepted). [PDF]
• Yuyang Xie, Jiezhong Qiu, Laxman Dhulipala, Wenjian Yu, Jie Tang, Richard Peng, and Chi Wang. Towards Lightweight and Automated Representation Learning System for Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2023 (to appear).
• Fanjin Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Bin Shao, Rui Li, and Kuansan Wang. OAG: Linking Entities across Large-Scale Heterogeneous Knowledge Graphs. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2023 (to appear).
• Zhenyu Hou, Yukuo Cen, Ziding Liu, Dongxue Wu, Baoyan Wang, Xuanhe Li, Lei Hong, and Jie Tang. MTDiag: An Effective Multi-Task Framework for Automatic Diagnosis. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI'23). [PDF]
• Ming Ding, Wendi Zheng, Wenyi Hong, and Jie Tang. CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers. In Proceedings of the Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS'22). [*Code&Data&Model*] [*Demo*]
• Zhenyu Hou, Xiao Liu, Yukuo Cen, Yuxiao Dong, Hongxia Yang, Chunjie Wang, and Jie Tang. GraphMAE: Self-Supervised Masked Graph Autoencoders. In Proceedings of the Twenty-Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'22). [PDF] [*Code&Data*]
• Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, and Jie Tang. Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries. In Proceedings of the Twenty-Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'22). [PDF] [*Code&Data*]
• Xiao Liu, Da Yin, Jingnan Zheng, Xingjian Zhang, Peng Zhang, Hongxia Yang, Yuxiao Dong, and Jie Tang. OAG-BERT: Towards a Unified Backbone Language Model for Academic Knowledge Services. In Proceedings of the Twenty-Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'22). [PDF] [*Code&Data*]
• Jifan Yu, Xiaohan Zhang, Yifan Xu, Xuanyu Lei, Xinyu Guan, Jing Zhang, Lei Hou, Juanzi Li, and Jie Tang. XDAI: A Tuning-free Framework for Exploiting Pre-trained Language Models in Knowledge Grounded Dialogue Generation. In Proceedings of the Twenty-Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'22). [PDF] [*Demo*]
• Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael Mahoney, and Alvin Cheung. GACT: Activation Compressed Training for Generic Network Architectures. In Proceedings of the 39th International Conference on Machine Learning (ICML'22). [PDF]
• Ziang Li, Ming Ding, Weikai Li, Zihan Wang, Ziyu Zeng, Yukuo Cen, and Jie Tang. Rethinking the Setting of Semi-supervised Learning on Graphs. In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI'22). [PDF] [*Code&Data*]
• Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, and Jie Tang. GLM: General Language Model Pretraining with Autoregressive Blank Infilling. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (ACL'22). [PDF] [*Code&Data*]
• Xiao Liu, Kaixuan Ji, Yicheng Fu, Weng Lam Tam, Zhengxiao Du, Zhilin Yang, and Jie Tang. P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (ACL'22). [PDF] [*Code&Data*]
• Yanan Zheng, Jing Zhou, Yujie Qian, Ming Ding, Chonghua Liao, Jian Li, Ruslan Salakhutdinov, Jie Tang, Sebastian Ruder, and Zhilin Yang. FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (ACL'22). [PDF] [*Code&Data*] [LeaderBoard]
• Jing Zhou, Yanan Zheng, Jie Tang, Jian Li, and Zhilin Yang. FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (ACL'22). [PDF] [*Code&Data*]
• Jing Zhang, Xiaokang Zhang, Jifan Yu, Jian Tang, Jie Tang, Cuiping Li, and Hong Chen. Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (ACL'22). [PDF] [*Code&Data*]
• Chenguang Wang, Xiao Liu, Zui Chen, Haoyun Hong, Jie Tang, and Dawn Song. DeepStruct: Pre-Training of Language Models for Structure Prediction. In Proceedings of the 60th Annual Meeting of the Association of Computational Linguistics (Findings of ACL'22).
• Bo Chen, Jing Zhang, Xiaokang Zhang, Yuxiao Dong, Jian Song, Peng Zhang, Kaibo Xu, Evgeny Kharlamov, and Jie Tang. GCCAD: Graph Contrastive Learning for Anomaly Detection. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2022 (accepted).
• Zhen Yang, Ming Ding, Xu Zou, Jie Tang, Bin Xu, Chang Zhou, and Hongxia Yang. Region or Global? A Principle for Negative Sampling in Graph-based Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2022 (accepted). [PDF] [*Code&Data*]
• Wenzheng Feng, Yuxiao Dong, Huang Tinglin, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, and Jie Tang. GRAND+: Scalable Graph Random Neural Networks. In Proceedings of the Web Conference 2022 (WWW'22) (accepted). [PDF] [*Code&Data*]
• Xiao Liu, Haoyun Hong, Xinghao Wang, Zeyi Chen, Evgeny Kharlamov, Yuxiao Dong, and Jie Tang. SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs. In Proceedings of the Web Conference 2022 (WWW'22) (accepted). [PDF] [*Code&Data*] (Best Paper Candidate)
• Zhen Yang, Ming Ding, Bin Xu, Hongxia Yang, and Jie Tang. STAM: A Spatiotemporal Aggregation Method for Graph Neural Network-based Recommendation. In Proceedings of the Web Conference 2022 (WWW'22). [PDF] [*Code&Data*]
• 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, and Wenguang Chen. BAGUALU: Targeting Brain Scale Pretrained Models with over 37 Million Cores. In Proceedings of the 27th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming (PPoPP'22). [PDF]
• Bo Chen, Jing Zhang, Xiaokang Zhang, Xiaobin Tang, Lingfan Cai, Hong Chen, Cuiping Li, Peng Zhang, and Jie Tang. CODE: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking. In Proceedings of the 36rd AAAI Conference on Artificial Intelligence (AAAI'22). [PDF] [*Code&Data*]
• Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, and Jie Tang. CogView: Mastering Text-to-Image Generation via Transformers. In Proceedings of the Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS'21). [PDF] [*Code&Data&Model*] [*Demo*]
• Jialin Zhao, Yuxiao Dong, Ming Ding, Evgeny Kharlamov, and Jie Tang. Adaptive Diffusion in Graph Neural Networks. In Proceedings of the Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS'21). [PDF] [*Code&Data*]
• Yi Ma, Xiaotian Hao, Jianye HAO, Jiawen Lu, Xing Liu, Xialiang Tong, Mingxuan Yuan, Zhigang Li, Zhaopeng Meng, and Jie Tang. A Reinforcement Learning Based Bi-level Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems. In Proceedings of the Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS'21). [PDF]
• Zhu Zhang, Jianxin Ma, Chang Zhou, Rui Men, Zhikang Li, Ming Ding, Jie Tang, Jingren Zhou, and Hongxia Yang. UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis. In Proceedings of the Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS'21). [PDF]
• Qinkai Zheng, Xu Zou, Yuxiao Dong, Yukuo Cen, Da Yin, Jiarong Xu, Yang Yang, and Jie Tang. Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning. In Proceedings of the Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS'21). (NeurIPS 2021 Datasets and Benchmarks) [PDF] [*Code&Data*]
• Shu Zhao, Ziwei Du, Jie Chen, Yanping Zhang, Jie Tang, and Philip S. Yu. Hierarchical Representation Learning for Attributed Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [*Code&Data*]
• Zhenyu Hou, Yukuo Cen, Yuxiao Dong, Jie Zhang, and Jie Tang. Automated Unsupervised Graph Representation Learning. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [*Code&Data*]
• Zhengxiao Du, Chang Zhou, Jiangchao Yao, Teng Tu, Letian Cheng, Hongxia Yang, Jingren Zhou, and Jie Tang. CogKR: Cognitive Graph for Multi-hop Knowledge Reasoning. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [*Code&Data*]
• Jie Gong, Xiao Liu, and Jie Tang. How Monetary Incentives Improve Outcomes in MOOCs: Evidence from a Field Experiment. Journal of Economic Behavior and Organization (JEBO), 2021 (accepted). [PDF]
• Xiao Liu, Fanjin Zhang, Zhenyu Hou, Li Mian, Zhaoyu Wang, Jing Zhang, and Jie Tang. Self-supervised Learning: Generative or Contrastive. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [Arxiv] [*Slides*]
• Da Yin, Weng Lam Tam, Ming Ding, and Jie Tang. MRT: Tracing the Evolution of Scientific Publications. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [Slides_pptx] [Slides_pdf] [*System*]
• Xu Zou, Da Yin, Qingyang Zhong, Hongxia Yang, Zhilin Yang, and Jie Tang. Controllable Generation from Pre-trained Language Models via Inverse Prompting. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [*Code&Data&Model*] [*Demo*]
• Xu Zou, Qinkai Zheng, Yuxiao Dong, Xinyu Guan, Evgeny Kharlamov, Jialiang Lu, and Jie Tang. TDGIA: Effective Injection Attacks on Graph Neural Networks. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF]
• Qingsong Lv, Ming Ding, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Siming He, Chang Zhou, Jian-guo Jiang, Yuxiao Dong, and Jie Tang. Are we really making much progress? Revisiting, benchmarking and refining the Heterogeneous Graph Neural Networks. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [Slides_pdf] [*Code&Data*] [Leaderboard]
• Tinglin Huang, Yuxiao Dong, Ming Ding, Zhen Yang, Wenzheng Feng, Xinyu Wang, and Jie Tang. MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [*Code*]
• Junyang Lin, Rui Men, An Yang, Chang Zhou, Yichang Zhang, Peng Wang, Jingren Zhou, Jie Tang, and Hongxia Yang. M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF]
• Yuxuan Shi, Gong Cheng, Trung-Kien Tran, Jie Tang, and Evgeny Kharlamov. Keyword-Based Knowledge Graph Exploration Based on Quadratic Group Steiner Trees. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI'21). [PDF] [*Code*]
• Jiezhong Qiu, Laxman Dhulipala, Jie Tang, Richard Peng, and Chi Wang. LightNE: A Lightweight Graph Processing System for Network Embedding. In Proceedings of the 2021 ACM SIGMOD international conference on Management of data (SIGMOD'21), 2021. [PDF] [Slides_ppt] [Slides_pdf] [*Code*]
• Xiao Liu, Li Mian, Yuxiao Dong, Fanjin Zhang, Jing Zhang, Jie Tang, Peng Zhang, Jibing Gong, and Kuansan Wang. OAG_know: Self-supervised Learning for Linking Knowledge Graphs. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021. [PDF] [*Data*] [*Code*]
• 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, and Jun Zhu. Pre-Trained Models: Past, Present and Future. AI Open Journal, 2021. [PDF]
• Xueyi Liu and Jie Tang. Network Representation Learning: A Macro and Micro Outlook. AI Open Journal, 2021. [PDF] [Slides]
• Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang, Xiao Liu, Ruobing Xie, Kai Zhuang, Xu Zhang, Leyu Lin, and Philip S. Yu. Understanding WeChat User Preferences and “Wow” Diffusion. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021. [PDF] [Slides_ppt] [Slides_pdf] [*Code*] [*Data*]
• Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Evgeny Kharlamov, and Jie Tang. Graph Random Neural Networks for Semi-Supervised Learning on Graphs. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NeurIPS'20). [PDF] [Appendix] [*Code*]
• Ming Ding, Chang Zhou, Hongxia Yang, and Jie Tang. CogLTX: Applying BERT to Long Texts. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NeurIPS'20). [PDF] [*Code*] [*Data*]
• Jiezhong Qiu, Chi Wang, Ben Liao, Richard Peng, and Jie Tang. A Matrix Chernoff Bound for Markov Chains and its Application to Co-occurrence Matrices. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NeurIPS'20). [PDF] [Slides_ppt] [Slides_pdf]
• Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, and Jie Tang. Modelling High-Order Social Relations for Item Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2020 (accepted). [PDF]
• Bo Chen, Jing Zhang, Jie Tang, Lingfan Cai, Zhaoyu Wang, Shu Zhao, Hong Chen, and Cuiping Li. CONNA: Addressing Name Disambiguation on The Fly. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2020 (accepted). [PDF]
• Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, and Jie Tang. GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [Slides_ppt] [Slides_PDF] [*data & code*]
• Zhen Yang, Ming Ding, Chang Zhou, Hongxia Yang, Jingren Zhou, and Jie Tang. Understanding Negative Sampling in Graph Representation Learning. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [Slides_ppt] [Slides_PDF] [*data & code*]
• Yukuo Cen, Jianwei Zhang, Xu Zou, Chang Zhou, Hongxia Yang, and Jie Tang. Controllable Multi-Interest Framework for Recommendation. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [*data & code*]
• Jibing Gong, Shen Wang, Jinlong Wang, Hao Peng, Wenzheng Feng, Dan Wang, Yi Zhao, Huanhuan Li, Jie Tang, and Philip Yu. Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. In Proceedings of the 43th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'20). [PDF]
• Yuxiao Dong, Ziniu Hu, Kuansan Wang, Yizhou Sun and Jie Tang. Heterogeneous Network Representation Learning. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI'20). [PDF] [Slides_PPT] [Slides_PDF] [Poster]
• Jifan Yu, Gan Luo, Tong Xiao, Qingyang Zhong, Yuquan Wang, wenzheng feng, Junyi Luo, Chenyu Wang, Lei Hou, Juanzi Li, Zhiyuan Liu and Jie Tang. MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs. In Proceedings of the 58th Annual Meeting of the Association of Computational Linguistics (ACL'20). [PDF] [*data & code*]
• Si Zhang, Hanghang Tong, Jie Tang, Jiejun Xu, and Wei Fan. Incomplete Network Alignment: Problem Definitions and Fast Solutions. ACM Transactions on Knowledge Discovery from Data (TKDD), 2020, accepted. [PDF]
• Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, and Jie Tang. Cognitive Graph for Multi-Hop Reading Comprehension at Scale. In Proceedings of the 57th Annual Meeting of the Association of Computational Linguistics (ACL'19). [PDF] [*data & code*]
• Jifan Yu, Chenyu Wang, Gan Luo, Lei Hou, Juanzi Li, Jie Tang, and Zhiyuan Liu. Course Concept Expansion in MOOCs with External Knowledge and Interactive Game. In Proceedings of the 57th Annual Meeting of the Association of Computational Linguistics (ACL'19). [PDF] [data & code]
• Fanjin Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Bin Shao, Rui Li, and Kuansan Wang. OAG: Toward Linking Large-scale Heterogeneous Entity Graphs. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data] [code] [code]
• Xichen Ding, Jie Tang, Tracy Liu, Cheng Xu, Yaping Zhang, Feng Shi, Qixia Jiang and Dan Shen. Infer Implicit Contexts in Real-time Online-to-Offline Recommendation. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF]
• Yukuo Cen, Xu Zou, Jianwei Zhang, Hongxia Yang, Jingren Zhou and Jie Tang. Representation Learning for Attributed Multiplex Heterogeneous Network. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data & code]
• Qibin Chen, Junyang Lin, Yichang Zhang, Hongxia Yang, Jingren Zhou and Jie Tang. Towards Knowledge-Based Personalized Product Description Generation in E-commerce. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data & code]
• Zhengxiao Du, Xiaowei Wang, Hongxia Yang, Jingren Zhou and Jie Tang. Sequential Scenario-Specific Meta Learner for Online Recommendation. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF]
• Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, and Jie Tang. NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization. In Proceedings of the Web Conference 2019 (WWW'19) (accepted). [PDF] [*data & code*] (Best Paper Candidate)
• Yu Han, Jie Tang, and Qian Chen. Network Embedding under Partial Monitoring for Evolving Networks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF] [Slides_PPT] [Slides_PDF]
• Jie Zhang, Yuxiao Dong, Yan Wang, Jie Tang, and Ming Ding. ProNE: Fast and Scalable Network Representation Learning. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF] [*data & code*]
• Yifeng Zhao, Xiangwei Wang, Hongxia Yang, Le Song, and Jie Tang. Large Scale Evolving Graphs with Burst Detection. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF]
• Yukuo Cen, Jing Zhang, Gaofei Wang, Yujie Qian, Chuizheng Meng, Zonghong Dai, Hongxia Yang, and Jie Tang. Trust Relationship Prediction in Alibaba E-Commerce Platform. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
• Fuli Feng, Xiangnan He, Jie Tang, and Tat-Seng Chua. Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
• Zhengxiao Du, Jie Tang, and Yuhui Ding. POLAR++: Active One-shot Personalized Article Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
• Wenzheng Feng, Jie Tang, Tracy Xiao Liu, Shuhuai Zhang, and Jian Guan. Understanding Dropouts in MOOCs. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19). [PDF] [data & code]
• Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, and Jie Tang. Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec. In Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining (WSDM'18). [PDF] [Slides] [*code*]
• Yi Qi, Qingyun Wu, Hongning Wang, Jie Tang, and Maosong Sun. Bandit Learning with Implicit Feedback. In Proceedings of the Thirty-Second Annual Conference on Neural Information Processing Systems (NeurIPS'18). [PDF]
• Yutao Zhang, Fanjin Zhang, Peiran Yao, and Jie Tang. Name Disambiguation in AMiner: Clustering, Maintenance, and Human in the Loop. In Proceedings of the Twenty-Forth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18). [PDF] [slides] [poster] [data & code] [video]
• Jiezhong Qiu, Jian Tang, Hao Ma, Yuxiao Dong, Kuansan Wang, and Jie Tang. DeepInf: Social Influence Prediction with Deep Learning. In Proceedings of the Twenty-Forth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18). [PDF] [poster] [data & code] [video]
• Yujie Qian, Jie Tang, and Kan Wu. Weakly Learning to Match Experts in Online Community. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF] [slides]
• Kan Wu, Jie Tang, and Chenhui Zhang. Where have you been? Inferring career trajectory from academic social network. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF] [slides]
• Tiancheng Shen, Jia Jia, Guangyao Shen, Fuli Feng, Xiangnan He, Huanbo Luan, Jie Tang, Tatseng Chua, Thanassis Tiropanis, and Wendy Hall. Cross-Domain Depression Detection via Harvesting Social Media. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF]
• Xiaotao Gu, Hong Yang, Jie Tang, Jing Zhang, Fanjin Zhang, Debing Liu, Wendy Hall, and Xiao Fu. Profiling Web Users Using Big Data. Social Network Analysis and Mining (SNAM), 2018, Volume 8, Issue 1, Pages 24:1-17.. [PDF]
• Hong Huang, Yuxiao Dong, Jie Tang, Hongxia Yang, Nitesh V. Chawla, and Xiaoming Fu. Will Triadic Closure Strengthen Ties in Social Networks? ACM Transactions on Knowledge Discovery from Data (TKDD), 2018, Volume 12, Issue 3, Article No. 30. [PDF]
• Yutao Zhang, Robert Chen, Jie Tang, Jimeng Sun, and Walter Stewart. LEAP: Learning to Prescribe Effective and Safe Treatment Combinations for Multimorbidity. In Proceedings of the Twenty-Third ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'17), pages 1315-1324. [PDF]
• Yu Han, Jie Tang, Hao Ye, and Bo Chen. Who to Invite Next? Predicting Invitees of Social Groups. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), pages 921-925. [PDF]
• Liangming Pan, Chengjiang Li, Juanzi Li, and Jie Tang. Prerequisite Relation Learning for Concepts in MOOCs. In Proceedings of the 55th Annual Meeting of the Association of Computational Linguistics (ACL'17), pages 1447-1456. [PDF] [Data&Code]
• Jie Tang. Computational Models for Social Network Analysis: A Brief Survey. In Proceedings of the Twenty-Sixth World Wide Web Conference (WWW'17), pages 921-925. [PDF] [Slides_PPT]
• Jing Zhang, Jie Tang, Cong Ma, Hanghang Tong, Yu Jing, Juanzi Li, Walter Luyten, and Marie-Francine Moens. Fast and Flexible Top-k Similarity Search on Large Networks. ACM Transactions on Information Systems (TOIS), 2017, Volume 36, Issue 2, Article No. 13. [PDF]
• Lei Hou, Juanzi Li, Xiao-Li Li, Jie Tang, and Xiaofei Guo. Learning to Align Comments to News Topics. ACM Transactions on Information Systems (TOIS), 2017, Volume 36, Issue 1, Article No. 9. [PDF]
• Yang Yang, Jie Tang, and Juanzi Li. Learning to Infer Competitive Relationships in Heterogeneous Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), 2018, Volume 12 Issue 1, Article No. 12. [PDF]
• Huijie Lin, Jia Jia, Jiezhong Qiu, Yongfeng Zhang, Guangyao Shen, Lexing Xie, Jie Tang, Ling Feng, and Tat-Seng Chua. Detecting Stress Based on Social Interactions in Social Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2017, Volume 29, Issue 9, Pages 1820-1833. [PDF]
• Yuxiao Dong, Nitesh V. Chawla, Jie Tang, Yang Yang, and Yang Yang. User Modeling on Demographic Attributes in Large-Scale Mobile Social Networks. ACM Transactions on Information Systems (TOIS), 2017, Volume 35, Issue 4, Article No. 35. [PDF]
• Jie Tang and Wendy Hall. Cross-domain Ranking via Latent Space Learning. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 2618-2624. [PDF] [Slides_PPT] [Poster]
• Jing Zhang, Jie Tang, Yuanyi Zhong, Yuchen Mo, Juanzi Li, Guojie Song, Wendy Hall, and Jimeng Sun. StructInf: Mining Structural Influence from Social Streams. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 73-79. [PDF] [Slides_PPT] [Poster]
• Yikang Shen, Wenge Rong, Nan Jiang, Baolin Peng, Jie Tang, Zhang Xiong. Word Embedding Based Correlation Model for Question/Answer Matching. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 3511-3517. [PDF]
• Liangyue Li, Yuan Yao, Jie Tang, Wei Fan, and Hanghang Tong. QUINT: On Query-Specific Optimal Networks. In Proceedings of the Twenty-Second ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16). [PDF] [Slides_PDF] [Data&Code]
• Zhilin Yang, Jie Tang, and William W. Cohen. Multi-Modal Bayesian Embeddings for Learning Social Knowledge Graphs. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16), pages 2287-2293. [PDF] [Slides_PPT] [Slides_PDF] [Thesis (in Chinese)]
• Jiezhong Qiu, Yixuan Li, Jie Tang, Zheng Lu, Hao Ye, Bo Chen, Qiang Yang, and John Hopcroft. The Lifecycle and Cascade of WeChat Social Messaging Groups. In Proceedings of the Twenty-Fifth World Wide Web Conference (WWW'16), pages 311-320. [PDF] [Slides_PPT] [Slides_PDF]
• Jie Tang. AMiner: Toward Understanding Big Scholar Data. In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining (WSDM'16), pages 467-467. (Invited Talk) [PDF] [Slides_PPT] [Slides_PDF]
• Yang Yang, Jia Jia, Boya Wu, and Jie Tang. Social Role-Aware Emotion Contagion in Image Social Networks. In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), pages 65-71. [PDF] [Supplementary materials] [Slides_PPT] [Slides_PDF]
• Zhiyuan Wang, Yun Zhou, Jie Tang, and Jar-Der Luo. The Prediction of Venture Capital Co-Investment Based on Structural Balance Theory. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2016, Volume 28, Issue 2, Pages 537-550. [PDF]
• Jie Tang, Tiancheng Lou, Jon Kleinberg, and Sen Wu. Transfer Learning to Infer Social Ties across Heterogeneous Networks. ACM Transactions on Information Systems (TOIS), 2016, Volume 34, Issue 2, Article No. 7. [PDF] [Data&Code]
• Jie Tang and Juanzi Li. Semantic Mining of Social Networks. Morgan & Claypool Publishers, 2015. [DRAFT]
• Lei Shi, Hanghang Tong, Jie Tang, and Chuang Lin. VEGAS: Visual influEnce GrAph Summarization on Citation Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 12, Pages 3417-3431. [PDF] [Video Demo]
• Hong Huang, Jie Tang, Lu Liu, JarDer Luo, and Xiaoming Fu. Triadic Closure Pattern Analysis and Prediction in Social Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 12, Pages 3374-3389. [PDF]
• Jing Zhang, Zhanpeng Fang, Wei Chen, and Jie Tang. Diffusion of "Following" Links in Microblogging Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 8, Pages 2093-2106. [PDF]
• Jing Zhang, Jie Tang, Juanzi Li, Yang Liu, and Chunxiao Xing. Who Influenced You? Predicting Retweet via Social Influence Locality. ACM Transactions on Knowledge Discovery from Data (TKDD), 2015, Volume 9, Issue 3, Article No. 25. [PDF] [Code&Data]
• Jing Zhang, Jie Tang, Cong Ma, Hanghang Tong, Yu Jing, and Juanzi Li. Panther: Fast Top-k Similarity Search on Large Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1445-1454. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
• Yutao Zhang, Jie Tang, Zhilin Yang, Jian Pei, and Philip Yu. COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1485-1494. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
• Yu Han and Jie Tang. Probabilistic Community and Role Model for Social Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 407-416. [PDF] [Slides_PPT] [Slides_PDF] [Poster]
• Yuxiao Dong, Jing Zhang, Jie Tang, Nitesh V. Chawla, and Bai Wang. CoupledLP: Link Prediction in Coupled Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 199-208. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
• Yang Yang, Yizhou Sun, Jie Tang, Bo Ma, and Juanzi Li. Entity Matching across Heterogeneous Sources. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1395-1404. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
• Zhanpeng Fang and Jie Tang. Uncovering the Formation of Triadic Closure in Social Networks. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI'15), pages 2062-2068. [PDF] [Slides_PPT] [Slides_PDF] [Poster]
• Jie Tang, Zhanpeng Fang, and Jimeng Sun. Incorporating Social Context and Domain Knowledge for Entity Recognition. In Proceedings of the Twenty-Fourth World Wide Web Conference (WWW'15), pages 517-526. [PDF] [Slides_PPT] [Slides_PDF] [Code&Data]
• Jie Tang, Chenhui Zhang, Keke Cai, Li Zhang, and Zhong Su. Sampling Representative Users from Large Social Networks. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), pages 304-310. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
• Yang Yang, Jie Tang, Cane Wing-Ki Leung, Yizhou Sun, Qicong Chen, Juanzi Li, and Qiang Yang. RAIN: Social Role-Aware Information Diffusion. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), pages 367-373. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
• Yuxiao Dong, Yang Yang, Jie Tang, Yang Yang, and Nitesh V. Chawla. Inferring User Demographics and Social Strategies in Mobile Social Networks. In Proceedings of the Twentyth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'14), pages 15-24. [PDF] [Madness] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code] [Code Download] (Report by United Nations)
• Mi Zhang, Jie Tang, Xuchen Zhang, Xiangyang Xue. Addressing Cold Start in Recommender Systems: A Semi-supervised Co-training Algorithm. In Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'14), pages 73-82. [PDF]
• Jing Zhang, Jie Tang, Honglei Zhuang, Cane Wing-Ki Leung, and Juanzi Li. Role-aware Conformity Influence Modeling and Analysis in Social Networks. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 958-965. [PDF] [Poster] [Data&Code]
• Yang Yang, Jia Jia, Shumei Zhang, Boya Wu, Qicong Chen, Juanzi Li, Chunxiao Xing, and Jie Tang. How Do Your Friends on Social Media Disclose Your Emotions? In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 306-312. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code]
• Yang Yang, Walter Luyten, Lu Liu, Marie-Francine Moens, Jie Tang, and Juanzi Li. Forecasting Potential Diabetes Complications. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 313-319. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code]
• Zhigang Wang, Juanzi Li, Shuangjie Li, Mingyang Li, Jie Tang, Kuo Zhang, and Kun Zhang. Cross-lingual Knowledge Validation Based Taxonomy Derivation from Heterogeneous Online Wikis. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 180-186. [PDF] [Poster] [Data]
• Zhixin Li, Siqiang Wen, Juanzi Li, Peng Zhang, and Jie Tang. On Modelling Non-linear Topical Dependencies. In Proceedings of the 31st International Conference on Machine Learning (ICML'14), pages 458-466. [PDF]
• Hong Huang, Jie Tang, Sen Wu, Lu Liu, and Xiaoming Fu. Mining Triadic Closure Patterns in Social Networks. In Proceedings of the Twenty-Third World Wide Web Conference (WWW'14), pages 499-504. [PDF] [Slides_PPT] [Slides_PDF]
• Jie Tang, Sen Wu, and Jimeng Sun. Confluence: Conformity Influence in Large Social Networks. In Proceedings of the Ninteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'13), pages 347-355. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code] (Oral Presentation)
• Yizhou Sun, Jie Tang, Jiawei Han, Cheng Chen, and Manish Gupta. Co-Evolution of Multi-Typed Objects in Dynamic Star Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2014, Volume 26, Issue 12, Pages 2942-2955. [PDF]
• Yi Cai, Ho-fung Leung, Qing Li, Hao Han, Jie Tang, Juanzi Li. Typicality-based Collaborative Filtering Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2014, Volume 26, Issue 3, Pages 766-779. [PDF]
• Jing Zhang, Biao Liu, Jie Tang, Ting Chen, and Juanzi Li. Social Influence Locality for Modeling Retweeting Behaviors. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pages 2761-2767. [PDF] [Data&Code] [Poster]
• Lei Hou, Juanzi Li, Xiaoli Li, Jiangfeng Qu, Xiaofei Guo, Ou Hui, and Jie Tang. What Users Care about: a Framework for Social Content Alignment. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pages 1401-1407. [PDF] [Data & Readme] [Slides_PDF] [Poster]
• Tiancheng Lou and Jie Tang. Mining Structural Hole Spanners Through Information Diffusion in Social Networks. In Proceedings of the Twenty-Second World Wide Web Conference (WWW'13), pages 837-848. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
• Tiancheng Lou, Jie Tang, John Hopcroft, Zhanpeng Fang, Xiaowen Ding. Learning to Predict Reciprocity and Triadic Closure in Social Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), 2013, Volume 7, Issue 2, Article No. 5. [PDF] [Code&Data] [System]
• Jie Tang, Sen Wu, Jimeng Sun, and Hang Su. Cross-domain Collaboration Recommendation. In Proceedings of the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12), pages 1285-1293. [PDF] [Slides_PDF   Slides_PPT ] [Poster] [Data&Code] [System] [Video] (Full Presentation & Best Poster Award)
• Jie Tang, Bo Wang, Yang Yang, Po Hu, Yanting Zhao, Xinyu Yan, Bo Gao, Minlie Huang, Peng Xu, Weichang Li, and Adam K. Usadi. PatentMiner: Topic-driven Patent Analysis and Mining. In Proceedings of the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12), pages 1366-1374. [PDF] [Slides] [Poster] [System] [Video]
• Rui Yan, Congrui Huang, Jie Tang, Yan Zhang, and Xiaoming Li. To Better Stand on the Shoulder of Giants. In Proceedings of the 2012 ACM/IEEE Joint Conference on Digital Libraries (JCDL'12), pages 51-60. [PDF] (Nominated as Best Student Paper)
• Jie Tang, Tiancheng Lou, and Jon Kleinberg. Inferring Social Ties across Heterogeneous Networks. In Proceedings of the Fifth ACM International Conference on Web Search and Data Mining (WSDM'12), pages 743-752. (Plenary presentation) [PDF] [Slides] [Poster] [Data&Code]
• Jie Tang, Yuan Zhang, Jimeng Sun, Jinghai Rao, Wenjing Yu, Yiran Chen, and ACM Fong. Quantitative Study of Individual Emotional States in Social Networks. IEEE Transactions on Affective Computing (TAC), 2012, Volume 3, Issue 2, Pages 132-144. [PDF] (Selected as the Spotlight Paper. Available here)
• Jie Tang, A.C.M. Fong, Bo Wang, and Jing Zhang. A Unified Probabilistic Framework for Name Disambiguation in Digital Library. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2012, Volume 24, Issue 6, Pages 975-987. [PDF] [Data]
• Bing He, Jie Tang, Ying Ding, Huijun Wang, Yuyin Sun, Jae Hong Shin, Bin Chen, Ganesh Moorthy, Judy Qiu, Pankaj Desai, David J. Wild. Mining relational paths in integrated biomedical data. PLOS ONE, 2011, 6(12). [PDF]
• Jie Tang, Jing Zhang, Ruoming Jin, Zi Yang, Keke Cai, Li Zhang, and Zhong Su. Topic Level Expertise Search over Heterogeneous Networks. Machine Learning Journal, 2011, Volume 82, Issue 2, Pages 211-237. [PDF] [URL]
• Jie Tang, Limin Yao, Duo Zhang, and Jing Zhang. A Combination Approach to Web User Profiling. ACM Transactions on Knowledge Discovery from Data (TKDD), 2010, Volume 5, Issue 1, Article 2. [PDF]
• Wenbin Tang, Honglei Zhuang, and Jie Tang. Learning to Infer Social Ties in Large Networks. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'11), pages381-397. [PDF] [Slides] [Data&Code] (Best Student Paper Runner-up)
• Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, and Juanzi Li. Social Context Summarization. In Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'11), pages 255-264. [PDF]
• Chenhao Tan, Lillian Lee, Jie Tang, Long Jiang, Ming Zhou, and Ping Li. User-level sentiment analysis incorporating social networks. In Proceedings of the Seventeenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'11), pages 1397-1405. [PDF] [Poster] (Top 4 cited papers among all KDD 2011's papers, More...)
• Chenhao Tan, Jie Tang, Jimeng Sun, Quan Lin, and Fengjiao Wang. Social Action Tracking via Noise Tolerant Time-varying Factor Graphs. In Proceedings of the Sixteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10), pages 1049-1058. [PDF] [Slides] [Data&Code]
• Chi Wang, Jiawei Han, Yuntao Jia, Jie Tang, Duo Zhang, Yintao Yu, and Jingyi Guo. Mining Advisor-Advisee Relationships from Research Publication Networks. In Proceedings of the Sixteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10), pages 203-212. [PDF] [Slides] [System] [Data&Code]
• Jie Tang, Jimeng Sun, Chi Wang, and Zi Yang. Social Influence Analysis in Large-scale Networks. In Proceedings of the Fifteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'09), pages 807-816. [PDF] [Slides] [Data] [Code] (Top 4 cited papers among all papers published at KDD 2009-2013's, More...)
• Jie Tang, Jing Zhang, Limin Yao, Juanzi Li, Li Zhang, and Zhong Su. ArnetMiner: Extraction and Mining of Academic Social Networks. In Proceedings of the Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'08), pages990-998. [PDF] [Slides] [System] [API] [Citation Data] [DBLP Citation Data] [Author-Conference-Topic (ACT) Model (source code)] [More Data] (SIGKDD Test-of-Time Award, the 2nd most-cited paper among all KDD 2008's papers, More...)
• Jie Tang, Hang Li, Yunbo Cao, and Zhaohui Tang. Email Data Cleaning. In Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'05), pages 489-499. [PDF] [Slides]

Knowledge Graph

• Zhichun Wang, Juanzi Li, and Jie Tang. Boosting Cross-lingual Knowledge Linking via Concept Annotation. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pages 2733-2739. [PDF] [Poster]
• Zhigang Wang, Zhixing Li, Juanzi Li, Jie Tang, and Jeff Z. Pan. Transfer Learning Based Cross-lingual Knowledge Extraction for Wikipedia. In Proceedings of the 51th Annual Meeting of the Association of Computational Linguistics (ACL'13), pages 641-650. [PDF] [Data & Readme]
• Zhichun Wang, Juanzi Li, Zhigang Wang, and Jie Tang. Cross-lingual Knowledge Linking Across Wiki Knowledge Bases. In Proceedings of the Twenty-First World Wide Web Conference (WWW'12), pages 459-468. [PDF]
• Juanzi Li, Jie Tang, Yi Li, and Qiong Luo. RiMOM: A Dynamic Multi-Strategy Ontology Alignment Framework. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2009, Volume 21, Issue 8, Pages 1218-1232. (if =2.236) [PDF] [URL] (The 2nd most-cited paper among TKDE 2009-13's 500+ papers, More...)
• Jie Tang, Ho-fung Leung, Qiong Luo, Dewei Chen, and Jibing Gong. Towards Ontology Learning from Folksonomies. In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI'09), pages 2089-2095. [PDF] [Slides]
• Qian Zhong, Hanyu Li, Juanzi Li, Guotong Xie, Jie Tang, and Lizhu Zhou. A Gauss Function based Approach for Unbalanced Ontology Matching. In Proceedings of the 2009 ACM SIGMOD international conference on Management of data (SIGMOD'09), pages 669-680. [PDF] [Slides]
• Feng Shi, Juanzi Li, and Jie Tang. Actively Learning Ontology Matching via User Interaction. In Proceedings of the 8th International Conference of Semantic Web (ISWC'09), pages 585-600. [PDF] [Slides]
• Jie Tang, Mingcai Hong, Juanzi Li, and Bangyong Liang. Tree-Structured Conditional Random Fields for Semantic Annotation. In Proceedings of the 5th International Conference of Semantic Web (ISWC'06), pages 640-653 [PPT] [PDF]
• Jie Tang, Juanzi Li, Bangyong Liang, Xiaotong Huang, Yi Li, and Kehong Wang. Using Bayesian Decision for Ontology Mapping. Journal of Web Semantics, 2006, Volume 4, Issue 4, Pages 243-262. (if =3.41) [URL] [PDF] (Top 8 cited papers in JWS's history, More...)

SERVICES   Go Top

• Editor-in-Chief (EiC) of IEEE Transactions on Big Data (IEEE TBD)
• Editor-in-Chief (EiC) of ai open---a new AI journal for open and sharing
• Associate Editor:
  • IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE)
  • ACM Transaction on Knowledge Discovery from DATA (ACM TKDD)
  • ACM Transactions on Intelligent Systems and Technology (ACM TIST)
  • Data Mining and Knowledge Discovery
  • Science China
  • Social Network Analysis and Mining Journal (SNAM)
• Past Associate Editor:
  • Semantic Web Journal (SWJ)
• Conference/Workshop Organization:
  • General Co-Chair of The Web Conference 2023 (WWW'23)
  • General Co-Chair of The 21st IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'22)
  • Program Co-Chair of The Web Conference 2021 (WWW'21)
  • General Co-Chair of the 24th Conference on Innovation in Clouds, Internet and Networks (ICIN'21)
  • Tutorial Co-Chair of The Web Conference 2020 (WWW'20)
  • KDDCUP Co-Chair of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'20)
  • Sponsor Co-Chair of The Web Conference 2019 (WWW'19)
  • Program Co-Chair of The 8th CCF International Conference on Natural Language Processing and Chinese Computing (NLPCC'19)
  • Associate General Chair of the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'18)
  • "Sister Conference Best Paper Track" Chair of the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI'18)
  • AI Web Track (Intelligent and Autonomous systems on the Web) Chair of the 27th International Conference on World Wide Web (WWW'18)
  • Video and Streaming Co-Chair of the 23th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'17)
  • Research Track Program Co-Chair of the 25th ACM International Conference on Information and Knowledge Management (CIKM'16)
  • Video and Streaming Co-Chair of the 22th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'16)
  • Program Co-Chair of the 8th ACM International Conference on Web Search and Data Mining (WSDM'15)
  • Program Co-Chair of The 2015 International Conference on Social Network Analysis and Mining (ASONAM'15)
  • KDD CUP Co-Chair of the 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'15)
  • Poster Co-Chair of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'14)
  • Data Co-Chair of the 8th International AAAI Conference on Weblogs and Social Media (ICWSM'14)
  • Tutorial Co-Chair of the 7th ACM International Conference on Web Search and Data Mining (WSDM'14)
  • Workshop Co-Chair of The 2014 International Conference on Social Network Analysis and Mining (ASONAM'14)
  • Vice Program Co-Chair of the 12th IEEE International Conference on Data Mining (ICDM'13)
  • Tutorial and workshop organization chair of the 23th International Joint Conference on Artificial Intelligence (IJCAI'13)
  • Workshop Co-Chair of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'13)
  • Poster Co-Chair of the 12th IEEE International Conference on Data Mining (ICDM'13)
  • Workshop Co-Chair of the 7th ACM Conference on Recommender Systems (RecSys'13)
  • Tutorial Co-Chair of The 2013 International Conference on Social Network Analysis and Mining (ASONAM'13)
  • Local Chair of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'12)
  • Program Co-Chair of The 2012 International Conference on Social Informatics (SocInfo'12)
  • Tutorial Co-Chair of The 2012 International Conference on Social Network Analysis and Mining (ASONAM'12)
  • Publications Co-Chairs of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'11)
  • Program Chair of the 7th International Conference on Advanced Data Mining and Applications (ADMA'11)
  • Publicity Co-Chair of the 11th IEEE International Conference on Data Mining (ICDM'11)
  • Poster Chair of the 4th ACM International Conference on Web Search and Data Mining (WSDM'11)
  • Area Chair of the 2011 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'11)
  • Panel Chair of the 4th edition of the successful IEEE International Conferences on Cyber, Physical and Social Computing (CPSCom'11)
  • Publicity Co-Chair of the Third International Conference on Social Informatics (SocInfo'11)
  • Vice Program Chair of the 2011 IEEE/WIC/ACM International Conference on Web Intelligence (WI'11)
  • Vice Program Chair of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence (WI'10)
  • Registration Chair of ASWC'06
  • Co-Chair of Workshop SWSM'11 on SIGIR'11, MDS'11 on SIGKDD'11, LDMTA'11 on SIGKDD'11, LDMTA'10 on SIGKDD'10, LDMTA'09 on ICDM'09, SWSM'09 on CIKM'09, Financial Data Mining (FDM'09), SWSM'08 on WWW2008.
• (S)PC Member:
• 2022: SIGKDD'22 (SPC), ICML'22 (Area Chair), IJCAI'22 (Area Chair), WWW'20 (Track Chair), WSDM'22 (SPC), ICDM'15 (Area Chair), ECML/PKDD'21 (SPC)
• 2021: SIGKDD'21 (SPC), ICML'21 (Area Chair), NeurIPS'21 (Area Chair), IJCAI'21 (Area Chair), CIKM'21 (SPC), SDM'21 (SPC), ECML/PKDD'21 (SPC)
• 2020: SIGKDD'20 (SPC), SDM'20, ICML'21, ECML/PKDD'20 (SPC), WWW'20 (SPC), ASONAM'20
• 2019: SIGKDD'19 (SPC), NeurIPS'19, ICML'19, IJCAI'19 (SPC), WWW'19, WSDM'19 (SPC), ASONAM'19
• 2018: WSDM'18 (SPC), IJCAI'18, SIGIR'18,
• 2017: SIGKDD'17 (SPC), AAAI'17 (SPC), ICWSM'17 (SPC), WSDM'17 (SPC), WWW'17, IJCAI'17, SIGIR'17
• 2016: SIGKDD'16 (SPC), WSDM'16, ICWSM'16 (SPC), ASONAM'16
• 2015: SIGKDD'15 (SPC), IJCAI'15 (SPC), ICWSM'15 (SPC), ICDM'15 (Area Chair), SDM'15, ICDE'15
• 2014: SIGKDD'14 (SPC), ICDM'14 (Area Chair), WSDM'14, SDM'14, ICWSM'14, ASONAM'14 (SPC)
• 2013: SIGKDD'13 (SPC), IJCAI'13 (SPC), WWW'13 (Social Networks, Content Analysis, Bridging structured and unstructured data), SIGIR'13, WSDM'13, SDM'13, ICWSM'13 (SPC), CIKM'13, SAC'13 (SPC), DASFAA'13.
• 2012: SIGKDD'12, WWW'12 (Tutorial, Web Mining, Social Networks, Demo), AAAI'12, SIGIR'12, ICDM'12, ICWSM'12 (SPC), ISWC'12 (SPC).
• 2011: SIGKDD'11, WWW'11, AAAI'11, WSDM'11, ICDM'11, ISWC'11 (SPC), ICMLA'11 (SPC), EMNLP'11, DASFAA'11, ASONAM'11, WAIM'11, DEXA'11.
• 2010: SIGKDD'10, SIGIR'10, WWW'10 (DM&ML track), ACL'10, COLING'10, ICDM'10, WSDM'10, ISWC'10, EMNLP'10, DASFAA'10, WI'10, DEXA'10, ISDPE'10, ASONAM'10, CloudCom'10, INCoS'10.
• 2009: SIGIR'09, SDM'09, DEXA'09, WISE'09, WI'09, IUI'09, ASONAM'09, ICCCI'09, NLPIR4DL'09, MCPC'09, CISIS'09, CASoN'09, APWeb-WAIM'09, KDIR'09, CloudCom'09, AIRS'09, ACM RecSys'09, SAW'09, ICIS'09, CSWS'09, WSM'09, WISM'09-AICI'09, ASWC'09, OEDM'09.
• 2008: IJCNLP'08, SAW'08, WWW'08 Poster Session, NIMC'08, SOCASE'08, PGSC'08, SNA-KDD'08, ASWC'08, WI'08, IWCSN'08, OAEI'08(SPC).
• 2007: SOCASE'07, PGSC'07, WI'07, OAEI'07 (SPC).

AWARDS AND HORNORS   Go Top

• 2020 Second State Science and Technology Prizes
• 2020 First Prize of Beijing Patent Award
• 2020 ACM SIGKDD Test-of-Time Award (*10-Year Best Paper Award*)
• 2020 WangXuan Distinguished Young Scholar
• 2018 ACM SIGKDD Service Award
• 2018 NSFC Distinguished Young Scholar
• 2017 First Prize of Beijing Science and Technology
• 2016 Microsoft Research Asia Collaborative Research Award
• 2015 Newton Advanced Fellowship Award
• 2013 First Prize of Chinese Association of AI (CAAI)
• 2012 CCF Young Scientist Award 
• 2012 NSFC Excellent Young Scholar
• 2011 Beijing Science and Technology Star
• 2011 SCOPUS National Youth Science Star
• 2010 IBM Scalable Data Analytics Innovation Faculty Award 
• 2010 Tsinghua Academic New Star Award
• 2012 JCDL Best Student Paper Nomination
• 2011 PKDD Best Student Paper Runnerup
• 2016 Best employee of DCST, Tsinghua University
• 2012 Best employee of DCST, Tsinghua University
• 2011 Best employee of Tsinghua University
• 2011 Best employee of DCST, Tsinghua University
• 2007 Best employee of DCST, Tsinghua University
• The 2006 Excellent PhD Thesis of Tsinghua University

TALKS   Go Top

• Keynote about Representation Learning on Networks to be given at ASONAM'19
• Keynote about AI driven MOOCs given at EDM'17
• Invited talk about academic knowledge graph given at WSDM'16
• Keynote about social network mining given at SocInfo'15

STUDENTS   Go Top

Post Doc

• Zhongyang Zhu
• Shaojiang Wang
• Yu Qiu
• Yunpeng Gao
• Jing Xu (Graduated)
• Sha Yuan (Leader @ BAAI)
• Yutao Zhang(CTO or Recurrent.ai)
• Huaiyu Wan (Assistant Professor @ Beijing Jiaotong University)
• Daifeng Li (Associate Professor @ Sun Yat-Sen University)

PhD Students

• Chenhui Zhang
• Jiezhong Qiu
• Wenzheng Feng
• Fanjin Zhang
• Aoao Feng
• Ming Ding
• Xu Zou
• Mengyang Sun
• Ming Zhou
• Yukuo Cen
• Zhengxiao Du
• Xu Cheng
• Kan Wu (Graduated)
• Yu Han (Graduated, Alibaba)
• Yutao Zhang (Graduated)
• Yang Yang (Assistant Professor @ Zhejiang University)
• Jing Zhang (Assistant Professor @ Renmin University)

Master Students

• Qingyang Zhong
• Kun Zhang
• Pengcheng Wang
• Alexandre Boulenger
• Yonglin Tan
• Xiaohan Zhang
• Qingsong Lv
• Jialin Zhao (graduated in 2021)
• Gan Luo (graduated in 2021)
• Vincent Couverchel (graduated in 2019)
• Valentin Kao (graduated in 2019)
• Da Yin (graduated in 2021)
• Yan Wang (M) (graduated in 2020)
• Runzhi Gao (graduated in 2021)
• Yan Wang (F) (graduated in 2019)
• Jie Zhang (graduated in 2019)
• Zhenhuan Chen (graduated in 2019)
• Yifeng Zhao (graduated in 2019)
• Mogford Michael (graduated in 2019)
• Ben Keller (graduated in 2019)
• Rytis Kumpa (graduated in 2019)
• Zhengyang Song (graduated in 2019)
• Ziwu Sun (graduated in 2018)
• Chaoyang Li (graduated in 2018)
• Xiaochen Wang (graduated in 2018)
• Fang Zhang (graduated in 2018)
• Tianji Zhao (graduated in 2017)
• Hong Yang (graduated in 2017, Assistant Professor @ Qinghai University)
• Zhanpeng Fang (graduated in 2016, Google US)
• Mu Yang (graduated in 2016, CTO @ Face++)
• Wenbin Tang (graduated in 2013, CTO @ Face++)
• Marcel Lee (graduated in 2013)
• Lenin Mookiah (graduated in 2013, PhD @ Tennessee Technological University)
• Yongliang Zhu (graduated in 2012, work @ Fuzhou)
• Wenyuan Xu (graduated in 2012)
• Zi Yang (graduated in 2011, now PhD at CMU)
• Limin Yao (co-advisor, graduated in 2008, @Twitter)
• Duo Zhang (co-advisor, graduated in 2007, @Twitter...)

Undergraduate Students
Here list those working with me for at least 8 months. I may miss some. Please let me know if you found.
If you want me to write a recommendation letter for you, please first read this.

• Current
• Aohan Zeng
• Wenyi Hong
• Zhuoyi Yang
• Ziang Li
• Zeyi Chen
• Shiyu Zhao
• Wendi Zheng
• Hanyu Lai
• Xiao Xia
• Xueyi Liu
• Xinghao Wang
• Haoyun Hong
• Yijia Xiao
• Yuxiang Chen
• Xingjian Zhang
• Zhibing Li
• Graduated in 2021
• Xiao Liu
• Zhenyu Hou
• Tianshu Yu
• Haojun Yu
• Shangqing Xu
• Niuniu Zhangli
• Kaiyuan Chen
• Graduated in 2020
• Zhengxiao Du
• Qingyang Zhong
• Yihan Wang
• Jiaqi Wang
• Han Yu
• Xiao Liu
• Kaiyuan Xu
• Li Mian
• Zijun Yao
• Graduated in 2019
• Peiran Yao
• Qibin Chen
• Yonglin Tan
• Minda Hu
• Zhicong Fang
• Zhuoyue Xiao
• Yuhui Ding
• Jianan Yao
• Chenyu Wang
• Junlin Song
• Xi Chen
• Tong Xiao
• Graduated in 2018
• Da Yin
• Peiran Yao
• Gan Luo
• Ming Ding
• Yijian Qin
• Xinyang Zhang
• Yukuo Cen
• Yuanhang Zheng
• Lemeng Wu
• Yifan Liu
• Graduated in 2017
• Xiaotao Gu (PhD @ UIUC)
• Yujie Qian (PhD @ MIT)
• Shaoxiong Wang (PhD @ MIT)
• Miao Ren (MS @ CMU)
• Qian Zhang (MS @ UCLA)
• Sida Gao (MS @ CMU)
• Graduated in 2016
• Yuan Yuan (PhD @ MIT)
• Honghao Wei (MS @ Stanford)
• Fei Xia (PhD @ Stanford)
• Jingqing Zhang (PhD @ Imperial College London)
• Tianrun Li
• Jiaqi Ma (PhD @ Mitch)
• Shan Han
• Yu Xia (PhD @ MIT)
• Graduated in 2015
• Zhilin Yang (PhD at CMU)
• Xinyu Zhou (@Face++)
• Weiran He
• Cong Ma (PhD at Princeton)
• Xunkai Zhang (@Google US)
• Zhelun Wu
• Wei Huang (PhD @ Tsinghua)
• Ye Cao
• Graduated in 2014
• Qianru Zhu (MS at CMU)
• Yang Liu
• Yihan Sun (PhD at CMU)
• Yaohui Ye
• Ning Jiang (U Mitch)
• Chenran Guan (MS at CMU)
• Jingyuan Liu
• Graduated in 2013
• Honglei Zhuang (PhD at UIUC)
• Sen Wu (MS at Stanford)
• Zhanpeng Fang (MS at THU)
• Liangtao Zhang (Work)
• Bo Ma (MS at CMU)
• Wei Chen (MS at CMU)
• Graduated in 2012
• Xiaowen Ding (MS at CMU)
• Yanting Zhao (PhD at Columbia U.)
• Yu Zhao (MS at CMU)
• Cheng Chen (PhD at MIT)
• Lin Xu
• Hang Su (PhD at Georgia Tech.)
• Tian Li (Dartmouth College)
• Yuxiao Dong (PhD at Notre Dame U.)
• Yubing Dong (MS at USC)
• Graduated in 2011
• Yuan Zhang (PhD at MIT)
• Lixin Shi (PhD at MIT)
• Tao Lei (PhD at MIT)
• Xuezhi Wang (PhD at CMU)
• Yuan Du (MS at Columbia U.)
• Yiran Chen (PhD at MSU)
• Jingyi Guo (PhD at UMass)
• Rui Du (MS at CMU)
• Wenjing Yu (MS at USC)
• Haoquan Guo (MS at NYU)
• Graduated in 2010
• Ning Zhang (PhD at UC, Berkeley)
• Chenhao Tan (PhD at Cornell)
• Zhe Wang (work in Beijing)
• Graduated in 2009
• Chi Wang (PhD at UIUC)
• Fengjiao Wang (PhD at UIC)
• Graduated before 2009
• Liu Liu (CMU and now Google, US)
• Yize Li (UCSC, and now StumbleUpon, US)

Other students collaborated with me

• Ming Yin (2011, PhD at Havard)
• Yajie Miao (2011, PhD at CMU)

Last updated date: April 12, 2023, by Jie Tang.