Ph. D. in Computer Science, College of Information Science and Technology, Nankai University Tianjin, China, 2001 - 2006
B. S. in Computer Science, College of Information Science and Technology, Nankai University Tianjin, China, 1997 - 2001
Work Experience
Professor, School of Information, Renmin University of China Beijing, China, 2018 -
Researcher & Professor, Institute of Computing Technology, Chinese Academy of Sciences Beijing, China, 2014 - 2018
Researcher and Senior Researcher, Noah's Ark Lab, Huawei Technologies Hong Kong SAR, China, 2012 - 2014
Associate Researcher, Microsoft Research Asia (MSRA) Beijing, China, 2006 – 2012
RESEARCH INTERESTS
His research interests span the areas of intelligent information retrieval, recommender systems, and big data analysis. He has specific interests in reinforcement learning to rank, deep learning for semantic matching and relevance ranking, and casual inference in IR.
Teaching
Artificial Intelligence with Python Programming Langauge
Introduction to big data analysis
Intelligent Information Retrieval
PUBLICATIONS
2024
Tool Learning with Large Language Models: A Survey
Chen Xu, Xiaopeng Ye, Wenjie Wang, Liang Pang, Jun Xu and Tat-Seng Chua
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024, Best Paper Honorable Mention)
ReCODE: Modeling Repeat Consumption with Neural ODE
Sunhao Dai, Changle Qu, Sirui Chen, Xiao Zhang and Jun Xu
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024, Best Short Paper nominees)
Smooth Start: A Unified Approach for gradual transition from cold to old in Recommender Systems
Jianwen Yang, Xiao Zhang, Jun Xu
The 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024)
Logic Rules as Explanations for Legal Case Retrieval
ZhongXiang Sun, Kepu Zhang, Weijie Yu, Haoyu Wang and Jun Xu
In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pp. 10747–10759, Torino, Italia.
Counterfactual Reward Modification for Streaming Recommendation with Delayed Feedback
Xiao Zhang, Haonan Jia, Hanjing Su, Wenhan Wang, Jun Xu, Ji-Rong Wen
In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’21), July 11–15, 2021, Virtual Event, Canada.
Proceedings of the 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, Virtual, Online, China, 2020-7-25-2020-7-30
Proceedings of the 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, Virtual, Online, China
Ruqing Zhang, Jiafeng Guo, Yanyan Lan, Jun Xu, Xueqi Cheng
Advances in Information Retrieval, ECIR. . ECIR 2018, LNCS 10772, pp. 289–302, 2018
Aggregating Neural Word Embeddings for Document Representation
Ruqing Zhang, Jiafeng Guo, Yanyan Lan, Jun Xu, Xueqi Cheng
Advances in Information Retrieval, ECIR. . ECIR 2018, LNCS 10772, pp. 303–315, 2018
Modeling the correlations of relations for knowledge graph embedding
Jizhao Zhu, Yantao Jia, Jun Xu, Qiao Jianzhong, and Xueqi Cheng
Journal of Computer Science and Technology, Volume 33, Issue 2, pp. 323–334, Mar. 2018.
Reinforcing Coherence for Sequence to Sequence Model in Dialogue Generation
Hainan Zhang, Yanyan Lan, Jiafeng Guo, Jun Xu, and Xueqi Cheng
Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI '18), Stockholm, Sweden, pp. 4567-4573, 2018.
Multi Page Search with Reinforcement Learning to Rank
Wei Zeng, Jun Xu, Yanyan Lan, Jiafeng Guo and Xueqi Cheng
Proceedings of the 4th ACM SIGIR Informational Conference on the Theory of Information Retrieval (ICTIR '18). (accepted, pdf). .
MQGrad: Reinforcement Learning of Gradient Quantization in Parameter Server
Guoxin Cui, Jun Xu, Wei Zeng, Yanyan Lan, Jiafeng Guo and Xueqi Cheng
Proceedings of the 4th ACM SIGIR Informational Conference on the Theory of Information Retrieval (ICTIR '18). (accepted, pdf). .
Tailored Sequence to Sequence Models for Different Conversation Scenarios
Hainan Zhang, Yanyan Lan, Jiafeng Guo, Jun Xu, and Xueqi Cheng
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL '18), Melbourne, Australia, pp. 1479-1488, 2018.
Learning to Control the Specificity in Neural Response Generation
Ruqing Zhang, Jiafeng Guo, Yixing Fan, Yanyan Lan, Jun Xu, and Xueqi Cheng
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Melbourne, Australia (ACL '18), Melbourne, Australia, pp. 1108-1117, 2018.
Modeling Diverse Relevance Patterns in Ad-hoc Retrieval
Yixing Fan, Jiafeng Guo, Yanyan Lan, Jun Xu, Chengxiang Zhai, and Xueqi Cheng
Proceedings of the 41st annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '18), Ann Arbor, MI, USA, pp. 375-384, 2018.
Variance Reduction of Policy Gradient Bandit Problem via Antithetic Variates
Sihao Yu, Jun Xu, Yanyan Lan, Jiafeng Guo, and Xueqi Cheng
Proceedings of the 41st annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '18), Ann Arbor, MI, USA, pp. 885-888, 2018.
From Greedy Selection to Exploratory Decision-Making: Diverse Ranking with Policy-Value Networks
Yue Feng, Jun Xu, Yanyan Lan, Jiafeng Guo, Wei Zeng, and Xueqi Cheng
In Proceedings of the 41st annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2018), Ann Arbor, MI, USA, pp. 125-134, 2018.
2017
Locally Smoothed Neural Networks
Liang Pang, Yanyan Lan, Jun Xu, Jiafeng Guo, and Xueqi Cheng
Proceedings of the 9th Asian Conference on Machine Learning (ACML ’17), Seoul, Korea, pp. 177-191, 2017.
Directly Optimize Diversity Evaluation Measures: a New Approach to Search Result Diversification
Jun Xu, Long Xia, Yanyan Lan, Jiafeng Guo, and Xueqi Cheng
ACM Transactions on Intelligent Systems and Technology (TIST), Volume 8, Issue 3, Article 41, pp. 41:1-41:26, Jan. 2017.
DeepRank: a New Deep Architecture for Relevance Ranking in Information Retrieval
Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, and Xueqi Cheng
Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM '17), Singapore, pp. 257-266, 2017.
Learning Visual Features from Snapshots for Web Search
Yixing Fan, Jiafeng Guo, Yanyan Lan, Jun Xu, and Xueqi Cheng
Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM '17), Singapore, pp. 247-256, 2017. (CIKM 2017 Best Full Paper Runner-up, pdf).
Reinforcement Learning to Rank with Markov Decision Process
Wei Zeng, Jun Xu, Yanyan Lan, Jiafeng Guo, and Xueqi Cheng
Proceedings of the 40th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '17), Shinjuku, Tokyo, Japan, pp. 945-948, 2017. Short paper.
Adapting Markov Decision Process for Search Result Diversification
Long Xia, Jun Xu, Yanyan Lan, Jiafeng Guo, Wei Zeng, and Xueqi Cheng
Proceedings of the 40th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '17), Shinjuku, Tokyo, Japan, pp. 535-544, 2017.
Directly Optimize Diversity Evaluation Measures: a New Approach to Search Result Diversification
Jun Xu, Long Xia, Yanyan Lan, Jiafeng Guo, and Xueqi Cheng
ACM Transactions on Intelligent Systems and Technology (TIST), Vol. 8: No. 3, Article 41, pp 41:1-41:26.
Proceedings of the 25th International Joint Conference on Artificial Intelligence . (IJCAI '16), New York, USA, pp. 2922-2928, 2016.
A Study of MatchPyramid Models on Ad-hoc Retrieval
Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, Xueqi Cheng
Proceedings of the SIGIR 2016 Workshop on Neural Information Retrieval (Neu-IR), Pisa, Italy, 2016.
Modeling Document Novelty with Neural Tensor Network for Search Result Diversification
Long Xia, Jun Xu, Yanyan Lan, Jiafeng Guo, and Xueqi Cheng
Proceedings of the 39th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '16), Pisa, Italy, pp. 395-404, 2016. (pdf, source code).
Ease the Process of Machine Learning with Dataflow
Tianyou Guo, Jun Xu, Xiaohui Yan, Jianpeng Hou, Ping Li, Zhaohui Li, Jiafeng Guo, and Xueqi Cheng
Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM '16), Indianapolis, USA, pp. 2437-2440, 2016. Demo paper. (pdf, demo)
2015
A Probabilistic Model for Bursty Topic Discovery in Microblogs
Xiaohui Yan, Jiafeng Guo, Yanyan Lan, Jun Xu, and Xueqi Cheng
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI '15), Austin Texas, USA, pp. 353-359, 2015.
Learning Word Representations by Jointly Modeling Syntagmatic and Paradigmatic Relations
Fei Sun, Jiafeng Guo, Yanyan Lan, Jun Xu, and Xueqi Cheng
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference of the Asian Federation of Natural Language Processing (ACL-IJCNLP '15), Beijing, China, pp. 136-145, 2015.
Learning Hierarchical Representation Model for Next Basket Recommendation
Pengfei Wang, Jiafeng Guo, Yanyan Lan, Jun Xu, Shengxian Wan, and Xueqi Cheng
Proceedings of the 38th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '15), Santiago, Chile, pp. 403-412, 2015. (pdf, source code and data).
Learning Maximal Marginal Relevance Model via Directly Optimizing Diversity Evaluation Measures
Long Xia, Jun Xu, Yanyan Lan, Jiafeng Guo, and Xueqi Cheng
Proceedings of the 38th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '15), Santiago, Chile, pp. 113-122, 2015. (pdf, source code).
Modeling Parameter Interactions in Ranking SVM
Yaogong Zhang, Jun Xu, Yanyan Lan, Jiafeng Guo, Maoqiang Xie, Yalou Huang, and Xueqi Cheng
Proceedings of the 24th ACM International Conference on Information and Knowledge Management (CIKM '15), Melbourne, Australia pp. 1799-1802, 2015. short paper. (pdf, poster)
Next Basket Recommendation with Neural Networks
Shengxian Wan, Yanyan Lan, Pengfei Wang, Jiafeng Guo, Jun Xu, and Xueqi Cheng
Proceedings of the 9th ACM Conference on Recommender Systems (RecSys '15), Vienna, Austria, 2015. poster.. .
2014
User Message Model: A New Approach to Scalable User Modeling on Microblog
Quan Wang, Jun Xu, and Hang Li
Proceedings of the Tenth Asia Information Retrieval Societies Conference (AIRS '14), Kuching, Malaysia, pp. 209-220, 2014.
Ranking Optimization with Constraints
Fangzhao Wu, Jun Xu, Hang Li, and Xin Jiang
Proceedings of the 23rd ACM Conference on Information and Knowledge Management (CIKM '14), Shanghai, China, pp. 1049-1058, 2014.
Semantic Matching in Search
Hang Li and Jun Xu (2014)
Foundations and Trends in Information Retrieval: Vol. 7: No. 5, pp 343-469.
Group Matrix Factorization for Scalable Topic Modeling
Quan Wang, Zheng Cao, Jun Xu, and Hang Li
In Proceedings of the 35th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2012), Portland, Oregon, USA, pp. 375-384, 2012.
2011
Regularized Latent Semantic Indexing
Quan Wang, Jun Xu, Hang Li, and Nick Craswell
Proceedings of the 34th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '11), Beijing China, pp. 685-694, 2011. (pdf, source code).
A Kernel Approach to Addressing Term Mismatch
Jun Xu, Wei Wu, Hang Li, and Gu Xu
In Proceedings of the 20th international conference companion on World Wide Web (WWW 2011), Hyderabad India, pp. 153-154, 2011. (poster)
Regularized Latent Semantic Indexing
Quan Wang, Jun Xu, Hang Li, and Nick Craswell
In Proceedings of the 34th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2011), Beijing China, pp. 685-694, 2011.
Learning Robust Relevance Model for Search using Kernel Method
Wei Wu, Jun Xu, Hang Li, and Satoshi Oyama (2011)
Journal of Machine Learning Research (JMLR), Vol. 12: pp 1429-1458.
2010
LETOR: A Benchmark Collection for Research on Learning to Rank for Information Retrieval
Tao Qin, Tie-Yan Liu, Jun Xu, and Hang Li
Information Retrieval Journal, 2010.
Relevance Ranking using Kernels
Jun Xu, Hang Li, and Chaoliang Zhong
Proceedings of the 6th Asia Information Retrieval Societies Conference (AIRS '10), Taipei, Taiwan, pp. 1-12, 2010.
2008
Directly Optimizing Evaluation Measures in Learning to Rank
Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, and Wei-Ying Ma
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '08), Singapore, pp. 107-114, 2008.
Proceedings of SIGIR 2008 Workshop on Learning to Rank for Information Retrieval (LR4IR '08), Singapore, pp. 52-58, 2008.
Group-based Learning: A Boosting Approach
Weijian Ni, Jun Xu, Hang Li, and Yalou Huang
Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM '08), Napa Valley, California, pp. 1443-1444, 2008.
Directly Optimizing Evaluation Measures in Learning to Rank
Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, and Wei-Ying Ma
In Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2008), Singapore, pp. 107-114, 2008.
Jun Xu, Yunbo Cao, Hang Li, Nick Craswell, and Yalou Huang
Proceedings of the 29th European Conference on Information Retrieval (ECIR '07), Rome, Italy, pp. 629-636, 2007.
LETOR: Benchmarking Learning to Rank for Information Retrieval
Tie-Yan Liu, Jun Xu, Tao Qin, Wenying Xiong, and Hang Li
Proceedings of SIGIR 2007 Workshop on Learning to Rank for Information Retrieval (LR4IR '07), Amsterdam, The Netherlands, pp. 3-10, 2007.
AdaRank: A Boosting Algorithm for Information Retrieval
Jun Xu and Hang Li
Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '07), Amsterdam, The Netherlands, pp. 391-398, 2007.
Soft Computing - A Fusion of Foundations, Methodologies and Applications, Springer Berlin Heidelberg, Volume 11, Issue 4, pp. 369-373, 2006.
A Supervised Learning Approach to Search of Definitions
Jun Xu, Yunbo Cao, Hang Li, Min Zhao, and Yalou Huang
Journal of Computer Science and Technology (JCST), Vol. 21(3), pp. 439-449, 2006.
Adapting ranking SVM to document retrieval
Yunbo Cao, Jun Xu, Tie-Yan Liu, Hang Li, Yalou Huang, and Hsiao-Wuen Hon
Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '06), Seattle, Washington, USA, pp. 186-193, 2006.