World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
13160
World Ranking
4762
National Ranking
636

Overview

Jun Xu is affiliated with Renmin University of China and specializes in Computer Science, with a primary focus on Artificial Intelligence. Their research spans subfields including Computer Vision and Pattern Recognition, Information Systems, Molecular Biology, and Management Science and Operations Research. The scientist's work also covers diverse topics such as Topic Modeling, Recommender Systems and Techniques, Natural Language Processing Techniques, Advanced Graph Neural Networks, Advanced Bandit Algorithms Research, Multimodal Machine Learning Applications, and Speech and Dialogue Systems.

The scientist has published extensively, with a significant number of contributions to venues such as arXiv (Cornell University), ACM Transactions on Information Systems, SSRN Electronic Journal, Frontiers of Computer Science, and IET conference proceedings.

Recent papers authored or coauthored by Jun Xu include:

  • Knowledge Graph Grounded Goal Planning for Open-Domain Conversation Generation, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Deep Network for the Automatic Segmentation and Quantification of Intracranial Hemorrhage on CT, 2021, Frontiers in Neuroscience

Jun Xu frequently collaborates with researchers such as Ji-Rong Wen, Xiao Zhang, Zihua Si, Zhenhua Dong, and Zhongxiang Sun.

In addition to journal and conference papers, Jun Xu has book publications including:

  • The Future and FinTech, 2021, published by World Scientific

Best Publications

  • MSR-VTT: A Large Video Description Dataset for Bridging Video and Language

    Jun Xu;Tao Mei;Ting Yao;Yong Rui

  • AdaRank: a boosting algorithm for information retrieval

    Jun Xu;Hang Li

  • Adapting ranking SVM to document retrieval

    Yunbo Cao;Jun Xu;Tie-Yan Liu;Hang Li

  • LETOR: A benchmark collection for research on learning to rank for information retrieval

    Tao Qin;Tie-Yan Liu;Jun Xu;Hang Li

  • Text matching as image recognition

    Liang Pang;Yanyan Lan;Jiafeng Guo;Jun Xu

  • LETOR: Benchmark Dataset for Research on Learning to Rank for Information Retrieval

    Tie-Yan Liu;Jun Xu;Tao Qin;Wenying Xiong

  • Learning Hierarchical Representation Model for NextBasket Recommendation

    Pengfei Wang;Jiafeng Guo;Yanyan Lan;Jun Xu

  • A deep architecture for semantic matching with multiple positional sentence representations

    Shengxian Wan;Yanyan Lan;Jiafeng Guo;Jun Xu

  • Multivariate Time Series Imputation with Generative Adversarial Networks

    Yonghong Luo;Xiangrui Cai;Ying Zhang;Jun Xu

  • DeepRank: A New Deep Architecture for Relevance Ranking in Information Retrieval

    Liang Pang;Yanyan Lan;Jiafeng Guo;Jun Xu

  • Text Matching as Image Recognition

    Liang Pang;Yanyan Lan;Jiafeng Guo;Jun Xu

  • Semantic Matching in Search

    Hang Li;Jun Xu

  • Uncovering ChatGPT’s Capabilities in Recommender Systems

    Unknown

  • Learning Multimodal Attention LSTM Networks for Video Captioning

    Jun Xu;Ting Yao;Yongdong Zhang;Tao Mei

  • Directly optimizing evaluation measures in learning to rank

    Jun Xu;Tie-Yan Liu;Min Lu;Hang Li

  • Semantic Matching in Search

    Unknown

  • Match-SRNN: modeling the recursive matching structure with spatial RNN

    Shengxian Wan;Yanyan Lan;Jun Xu;Jiafeng Guo

  • Clinical Named Entity Recognition Using Deep Learning Models.

    Yonghui Wu;Min Jiang;Jun Xu;Degui Zhi

  • A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations

    Shengxian Wan;Yanyan Lan;Jiafeng Guo;Jun Xu

  • A Study of Neural Word Embeddings for Named Entity Recognition in Clinical Text.

    Yonghui Wu;Jun Xu;Min Jiang;Yaoyun Zhang

  • A Study of MatchPyramid Models on Ad-hoc Retrieval.

    Liang Pang;Yanyan Lan;Jiafeng Guo;Jun Xu

  • SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval

    Liang Pang;Jun Xu;Qingyao Ai;Yanyan Lan

  • Regularized latent semantic indexing

    Quan Wang;Jun Xu;Hang Li;Nick Craswell

  • Reinforcement Learning to Rank with Markov Decision Process

    Zeng Wei;Jun Xu;Yanyan Lan;Jiafeng Guo

  • A probabilistic model for bursty topic discovery in microblogs

    Xiaohui Yan;Jiafeng Guo;Yanyan Lan;Jun Xu

  • Match-SRNN: Modeling the Recursive Matching Structure with Spatial RNN

    Shengxian Wan;Yanyan Lan;Jun Xu;Jiafeng Guo

  • Learning to Control the Specificity in Neural Response Generation

    Ruqing Zhang;Jiafeng Guo;Yixing Fan;Yanyan Lan

  • Deep Learning for Matching in Search and Recommendation

    Jun Xu;Xiangnan He;Hang Li

  • Modeling Diverse Relevance Patterns in Ad-hoc Retrieval

    Yixing Fan;Jiafeng Guo;Yanyan Lan;Jun Xu

Frequent Co-Authors

Xueqi Cheng
Xueqi Cheng Chinese Academy of Sciences
Yanyan Lan
Yanyan Lan Chinese Academy of Sciences
Jiafeng Guo
Jiafeng Guo Chinese Academy of Sciences
Hang Li
Hang Li ByteDance
Ji-Rong Wen
Ji-Rong Wen Renmin University of China
Tie-Yan Liu
Tie-Yan Liu Microsoft (United States)
Nianwen Xue
Nianwen Xue Brandeis University
Nick Craswell
Nick Craswell Microsoft (United States)
Fei Sun
Fei Sun Institute Of Computing Technology
Jun Guo
Jun Guo Beijing University of Posts and Telecommunications

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