教育经历

  • 2001年 - 2006年 南开大学 博士
  • 1997年 - 2001年 南开大学 本科

工作经历

  • 2018年 - 至今 中国人民大学教授、博导,中国人民大学杰出学者特聘教授
  • 2014年 - 2018年 中国科学院计算技术研究所 研究员、博导;中国科学院大学 岗位教授
  • 2012年 - 2014年 华为(香港)诺亚方舟实验室 资深研究员
  • 2006年 - 2012年 微软亚洲研究院 副研究员

研究方向

信息检索,互联网搜索,机器学习,大数据分析

学生要求

学生能力培养目标:

(1) 科学素养培养:理解基本科学观点和科学探究过程,认识科学技术对人类生活工作所产生的影响;

(2) 专业能力培养:培养学生的科学研究能力(论文阅读、工作调研、问题分析、方法设计、实验分析、论文写作等)、系统研发能力(编程、系统设计、项目管理),结合学生的特长和兴趣为学生制定不同的培养计划;

欢迎各位有意向攻读硕士或博士学位的同学报考!

指导(包括联合指导)毕业的学生及去向:

1. 毕业博士:
* 俞蔚捷(对外经贸大学)
* 杨婧璇(腾讯,腾讯大咖)
* 曾玮(百度)
* 夏龙(百度)
* 孙飞(阿里巴巴,阿里星)

2. 毕业硕士:
* 薄琳(兵器工业部)
* 贾浩男(进出口银行)
* 陈思睿(出国攻读博士)
* 鲁宇婧(百度)
* 许珂瑞(字节跳动)
* 冯悦(伯明翰大学,讲师)
* 侯建鹏(谷歌)
* 郭天佑(阿里巴巴)
* 何逸轩(百度)
* 李萍(腾讯)
* 朱海帆(谷歌)
* 劳雅迪(Apple)


3. 访问学生:
* 李朝辉(Pennsylvania State University,攻读博士)

教授课程

  • 人工智能与Python程序设计(本科)
  • 大数据分析导论(本科)
  • 新生研讨课-智能时代的搜索与推荐(本科)
  • 数据科学导论(本科)
  • 智能信息检索(研究生)
  • 网络数据挖掘(研究生,国科大)
  • 机器学习方法(研究生,中科院计算所)

科研项目

  • 国家重点研发计划课题:面向民航与金融核心风险度量和预测应用验证;主持
  • 国家重点研发计划项目:面向多元化纠纷化解的智能法律助理和类案分析系统关键技术研究;主持
  • 国家自然科学基金面上项目:基于强化学习的信息检索排序模型研究;主持
  • 北京智源人工智能研究院智能信息检索与挖掘方向项目:交互式信息检索;主持
  • 中国人民大学新教师启动项目:面向网络搜索的强化排序学习模型研究;主持
  • 企业合作:主持多项企业委托项目,合作伙伴包括华为、阿里、腾讯、快手等
  • 开源系统:大数据分析系统EasyML https://github.com/ICT-BDA/EasyML,创始人

学术论文

2024
Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era
Sunhao Dai, Chen Xu, Shicheng Xu, Liang Pang, Zhenhua Dong, Jun Xu
The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024 Tutorial)

Neural Retrievers are Biased Towards LLM-Generated Content
Sunhao Dai, Yuqi Zhou, Liang Pang, Weihao Liu, Xiaolin Hu, Yong Liu, Xiao Zhang, Gang Wang, Jun Xu
The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)

Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time
Haiyuan Zhao, Guohao Cai, Jieming Zhu, Zhenhua Dong, Jun Xu, Ji-Rong Wen
The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)

Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method
Chen Yang, Sunhao Dai, Yupeng Hou, Xin Zhao, Jun Xu, SONG Yang, Hengshu Zhu
The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)

Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning
Jiakai Tang, Sunhao Dai, Zexu Sun, Xu Chen, Jun Xu, Wenhui Yu, Lantao Hu, Peng Jiang, Han Li
The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)

Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration
Sunhao Dai, Weihao Liu, Yuqi Zhou, Liang Pang, Rongju Ruan, Gang Wang, Zhenhua Dong, Jun Xu, Ji-Rong Wen
ACL Findings (2024)

Effective In-Context Example Selection through Data Compression
ZhongXiang Sun, Kepu Zhang, Haoyu Wang, Xiao Zhang, Jun Xu
ACL Findings (2024)

UniSAR: Modeling User Transition Behaviors between Search and Recommendation
Teng Shi, Zihua Si, Jun Xu, Xiao Zhang, Xiaoxue Zang, Kai Zheng, Dewei Leng, Yanan Niu and Yang Song
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024)

A Taxation Perspective for Fair Re-ranking
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)

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, short paper)

Invisible Relevance Bias: Text-Image Retrieval Models Prefer AI-Generated Images
Shicheng Xu, Danyang Hou, Liang Pang, Jingcheng Deng, Jun Xu, Huawei Shen and Xueqi Cheng
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024)

To Search or to Recommend: Predicting Open-App Motivation with Neural Hawkes Process
Zhongxiang Sun, Zihua Si, Xiao Zhang, Xiaoxue Zang, Yang Song, Hongteng Xu and Jun Xu
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024)

Explicitly Integrating Judgment Prediction with Legal Document Retrieval: A Law-Guided Generative Approach
Weicong Qin, Zelin Cao, Weijie Yu, Zihua Si, Sirui Chen and Jun Xu
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024)

Reinforcing Long-Term Performance in Recommender Systems with User-Oriented Exploration Policy
Changshuo Zhang, Sirui Chen, Xiao Zhang, Sunhao Dai, Weijie Yu, Jun Xu
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024)

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.
下载: 论文文档
链接: 链接

List-aware Reranking-Truncation Joint Model for Search and Retrieval-augmented Generation
Shicheng Xu, Liang Pang, Jun Xu, Huawei Shen, Xueqi Cheng
The ACM Web Conference 2024
下载: 论文文档
链接: 链接

FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval
Chen Xu, Jun Xu, Yiming Ding, Xiao Zhang, Qi Qi
The ACM Web Conference 2024
下载: 论文文档
链接: 链接

Modeling User Attention in Music Recommendation
Sunhao Dai, Ninglu Shao, Jieming Zhu, Xiao Zhang, Zhenhua Dong, Jun Xu, Quanyu Dai, Ji-Rong Wen
IEEE International Conference on Data Engineering (ICDE 2024)

Explainable Legal Case Matching via Graph Optimal Transport
Zhongxiang Sun, Weijie Yu, Zihua Si, Jun Xu, Zhenhua Dong, Xu Chen, Hongteng Xu, Ji-Rong Wen
IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 36, No. 6, pp. 2461-2475
下载: 论文文档
链接: 链接

2023
Reward Imputation with Sketching for Contextual Batched Bandits
Xiao Zhang, Ninglu Shao, Zihua Si, Jun Xu, Wenhan Wang, Hanjing Su, Ji-Rong Wen
the 37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023)
下载: 论文文档
链接: 链接

App搜索场景下的意图推荐方法研究
周雨琦,戴孙浩,张朝亮,王刚,户保田,徐君
第二十九届全国信息检索学术会议 (CCIR2023)

Reinforcement Re-ranking with 2D Grid-based Recommendation Panels
Sirui Chen, Xiao Zhang, Xu Chen, Zhiyu Li, Yuan Wang, Quan Lin, and Jun Xu
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region (SIGIR-AP ’23)
下载: 论文文档
链接: 链接

Unbiased Top-$k$ Learning to Rank with Causal Likelihood Decomposition
Haiyuan Zhao, Jun Xu, Xiao Zhang, Guohao Cai, Zhenhua Dong, Ji-Rong Wen
In Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region (SIGIR-AP ’23)
下载: 论文文档
链接: 链接

HyperBandit: Contextual Bandit with Hypernewtork for Time-Varying User Preferences in Streaming Recommendation
Chenglei Shen, Xiao Zhang, Wei Wei, Jun Xu
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023)
下载: 论文文档
链接: 链接

KuaiSAR: A Unified Search And Recommendation Dataset
Zhongxiang Sun, Zihua Si, Xiaoxue Zang, Dewei Leng, Yanan Niu, Yang Song, Xiao Zhang, Jun Xu
CIKM 2023 Resource Paper
下载: 论文文档
链接: 链接

Dually Enhanced Delayed Feedback Modeling for Streaming Conversion Rate Prediction
Sunhao Dai, Yuqi Zhou, Jun Xu, Ji-Rong Wen
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023)
下载: 论文文档
链接: 链接

Uncovering ChatGPT's Capabilities in Recommender Systems
Sunhao Dai, Ninglu Shao, Haiyuan Zhao, Weijie Yu, Zihua Si, Chen Xu, Zhongxiang Sun, Xiao Zhang and Jun Xu
RecSys 2023 Late Breaking Results (LBR) track
下载: 论文文档
链接: 链接

Syntactic-Informed Graph Networks for Sentence Matching
Chen Xu, Jun Xu, Zhenhua Dong, Ji-Rong, Wen
ACM Transactions on Information Systems (TOIS), Vol. 42, No. 2, Article 38
下载: 论文文档
链接: 链接

Uncovering User Interest from Biased and Noised Watch Time in Video Recommendation
Haiyuan Zhao, Lei Zhang, Jun Xu, Guohao Cai, Zhenhua Dong and Ji-Rong Wen
Proceedings of the 17th ACM Conference on Recommender Systems (RecSys 2023)
下载: 论文文档
链接: 链接

Controllable Multi-Objective Re-ranking with Policy Hypernetworks
Sirui Chen, Yuan Wang, Zijing Wen, Zhiyu Li, ChangShuo Zhang, Xiao Zhang, Lin Quan, Cheng Zhu, Jun Xu
KDD 2023 Applied Data Science (ADS) track
下载: 论文文档
链接: 链接

Conditional Counterfactual Causal Effect for Individual Attribution
Ruiqi Zhao, Lei Zhang, Shengyu Zhu, Zitong Lu, Zhenhua Dong, Chaoliang Zhang, Jun Xu, Zhi Geng, Yangbo He
Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence (UAI 2023, Poster Spotlight)
链接: 链接

ACRank: 在神经排序模型中引入检索公理知识
薄琳,庞亮,张朝亮,王钊伟,董振华,徐君,文继荣
计算机学报
下载: 论文文档
链接: 链接

When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation
Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Xiaoxue Zang, Yang Song, Kun Gai and Ji-Rong Wen
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023)
下载: 论文文档

Law Article-Enhanced Legal Case Matching: a Causal Learning Approach
Zhongxiang Sun, Jun Xu, Xiao Zhang, Zhenhua Dong, Ji-Rong Wen
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023)
下载: 论文文档

U-SetRank:基于注意力机制修正的SetRank纠偏
张乐凭,徐君,庞亮,董振华,文继荣
计算机研究与发展

Enhancing Recommendation with Search Data in a Causal Learning Manner
Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Yang Song, Xiaoxue Zang, Ji-Rong Wen
ACM Transactions on Information Systems (TOIS),Vol. 41, No. 4, Article 111
下载: 论文文档
链接: 链接

P-MMF: Provider Max-min Fairness Re-ranking in Recommender System
Chen Xu, Sirui Chen, Jun Xu, Weiran Shen, Xiao Zhang, Gang Wang, Zhenhua Dong
International World Wide Web Conference (WWW 2023, Spotlight / Best Paper Award Nomination)
下载: 论文文档
链接: 链接

Separating Examination and Trust Bias from Click Predictions for Unbiased Relevance Ranking
Haiyuan Zhao, Jun Xu, Xiao Zhang, Guohao Cai, Zhenhua Dong, Ji-Rong Wen
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (WSDM 2023)
下载: 论文文档
链接: 链接

基于多任务学习的倾向性得分预测算法
曹泽麟,徐君,董振华,文继荣
计算机研究与发展, 2023, 60(1): 85-94
下载: 论文文档
链接: 链接

2022
Variance reduction for deep Q-Learning using stochastic recursive gradient
Haonan Jia, Xiao Zhang, Jun Xu, Wei Zeng, Hao Jiang, Xiaohui Yan
Proceedings of the 29th International Conference on Neural Information Processing (ICONIP 2022)
下载: 论文文档
链接: 链接

Optimal Partial Transport Based Sentence Selection for Long-form Document Matching
Weijie Yu, Liang Pang, Jun Xu, Bing Su, Zhenhua Dong and Ji-Rong Wen
The 29th International Conference on Computational Linguistics (COLING ‘22)
下载: 论文文档

Semantic Sentence Matching via Interacting Syntax Graphs
Chen Xu, Jun Xu, Zhenhua Dong and Ji-Rong Wen
The 29th International Conference on Computational Linguistics (COLING ‘22)
下载: 论文文档

Dually Enhanced Propensity Score Estimation in Sequential Recommendation
Chen Xu, Jun Xu, Xu Chen, Zhenghua Dong, Ji-RongWen
Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM ’22)
下载: 论文文档
链接: 链接

A Tag-Based Post-Hoc Framework for Explainable Conversational Recommendation
Kerui Xu, Jun Xu, Sheng Gao, Si Li, Jun Guo, and Ji-Rong Wen
Proceedings of the 2022 ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR ’22)

Explainable Legal Case Matching via Inverse Optimal Transport-based Rationale Extraction
Weijie Yu, Zhongxiang Sun, Jun Xu, Zhenhua Dong, Xu Chen, Hongteng Xu, and Ji-RongWen
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22)

Counteracting User Attention Bias in Music Streaming Recommendation via Reward Modification
Xiao Zhang, Sunhao Dai, Jun Xu, Zhenhua Dong, Quanyu Dai, Ji-Rong Wen
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’22)
下载: 论文文档
链接: 链接

A Model-Agnostic Causal Learning Framework for Recommendation using Search Data
Zihua Si, Xueran Han, Xiao Zhang, Jun Xu, Yue Yin, Yang Song, Ji-Rong Wen
Proceedings of the ACM Web Conference 2022 (WWW ’22)
下载: 论文文档
链接: 链接

Distribution Distance Regularized Sequence Representation for Text Matching in Asymmetrical Domains
Weijie Yu , Chen Xu, Jun Xu , Liang Pang, and Ji-Rong Wen
IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING (TASLP), VOL. 30
下载: 论文文档
链接: 链接

2021
Adapting User Preference to Online Feedback in Multi-round Conversational Recommendation
Kerui Xu, Jingxuan Yang, Jun Xu, Sheng Gao, Jun Guo, Ji-Rong Wen
Proceedings of the 14th ACM International Conference on Web Search and Data Mining, pages 364–372
下载: 论文文档
链接: 链接

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.
下载: 论文文档

RLPS: A Reinforcement Learning–Based Framework for Personalized Search
Jing Yao, Zhicheng Dou, Jun Xu, Ji-Rong Wen
ACM Transactions on Information Systems (TOIS) 39 (3), 1-29
下载: 论文文档

Regret Bounds for Online Kernel Selection in Continuous Kernel Space
Xiao Zhang, Shizhong Liao, Jun Xu, Ji-Rong Wen
Proceedings of the AAAI Conference on Artificial Intelligence 35 (12)
下载: 论文文档

A Joint Model for Dropped Pronoun Recovery and Conversational Discourse Parsing in Chinese Conversational Speech
Jingxuan Yang, Kerui Xu, Jun Xu, Si Li, Sheng Gao, Jun Guo, Nianwen Xue, Ji-Rong Wen
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics, ACL 2021
下载: 论文文档

2020
RLPer: A Reinforcement Learning Model for Personalized Search
Yao, Jing; Dou, Zhicheng; Xu, Jun; Wen, Ji-Rong
29th International World Wide Web Conference, WWW 2020, Taipei, Taiwan, 2020-4-20 - 2020-4-24
下载: 论文文档

Transformer-GCRF: Recovering Chinese Dropped Pronouns with General Conditional Random Fields
Jingxuan Yang; Kerui Xu; Jun Xu; Si Li; Sheng GAO; Jun Guo; Ji-Rong Wen; Nianwen Xue
Findings of ACL: EMNLP 2020, Online, 2020-11-16
下载: 论文文档
链接: 链接

Wasserstein Distance Regularized Sequence Representation for Text Matching in Asymmetrical Domains
Yu, Weijie; Xu, Chen; Xu, Jun; Pang, Liang; Gao, Xiaopeng; Wang, Xiaozhao; Wen, Ji-Rong
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Online, 2020-11-16
下载: 论文文档
链接: 链接

SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval
Pang, Liang; Xu, Jun; Ai, Qingyao; Lan, Yanyan; Cheng, Xueqi; Wen, Jirong
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
下载: 论文文档
链接: 链接

模仿排序学习模型
曾玮; 俞蔚捷; 徐君; 兰艳艳; 程学旗
中文信息学报, 2020, 34(01): 97-105
下载: 论文文档

Deep Learning for Matching in Search and Recommendation
Xu, Jun; He, Xiangnan; Li, Hang
Foundations and Trends in Information Retrieval, 2020, 14(2-3): 102-288
下载: 论文文档
链接: 链接

Reinforcement Learning to Rank with Pairwise Policy Gradient
Xu, Jun; Wei, Zeng; Xia, Long; Lan, Yanyan; Yin, Dawei; Cheng, Xueqi; Wen, Ji-Rong
Proceedings of the 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, Virtual, Online, China
下载: 论文文档
链接: 链接

2019
Differentiated Distribution Recovery for Neural Text Generation
Li, Jianing ; Lan, Yanyan ; Guo, Jiafeng; Xu, Jun; Cheng, Xueqi
33rd AAAI Conference on Artificial Intelligence, 2019.1.27-2019.2.1
下载: 论文文档

HAS-QA: Hierarchical Answer Spans Model for Open-Domain Question Answering
Pang, Liang ; Lan, Yanyan ; Guo, Jiafeng; Xu, Jun; Su, Lixin; Cheng, Xueqi
33rd AAAI Conference on Artificial Intelligence, 2019.1.27-2019.2.1
下载: 论文文档

PSGAN: A Minimax Game for Personalized Search with Limited and Noisy Click Data
Shuqi Lu ; Zhicheng Dou; Jun Xu; Jian-Yun Nie; Ji-Rong Wen
The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019.7.21-2019.7.25
下载: 论文文档

Teaching Machines to Extract Main Content for Machine Reading Comprehension
Li, Zhaohui ; Feng, Yue; Xu, Jun; Guo, Jiafeng; Lan, Yanyan; Cheng, Xueqi
33rd AAAI Conference on Artificial Intelligence, 2019.1.27-2019.2.1
下载: 论文文档

Name Entity Recognition with Policy-Value Networks
Yadi Lao ; Jun Xu ; Sheng Gao; Jun Guo; Ji-Rong Wen
42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), 2019.7.21-2019.7.25
下载: 论文文档

Modeling the Parameter Interactions in Ranking SVM with Low-Rank Approximation
Jun Xu, Wei Zeng, Yanyan Lan, Jiafeng Guo, and Xueqi Cheng (2019)
IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 31: No. 6, pp 1181-1193.
下载: 论文文档

2018
Neighborhood Voting: A Novel Search Scheme for Hashing
Yan Xiao; Jiafeng Guo; Yanyan Lan; Jun Xu; Xueqi Cheng
The 27th ACM International Conference on Information and Knowledge Management (CIKM 2018), 2018
下载: 论文文档

Question Headline Generation for News Articles
Ruqing Zhang ; Jiafeng Guo; Yixing Fan; Yanyan Lan; Jun Xu; Huanhuan Cao; Xueqi Cheng
The 27th ACM International Conference on Information and Knowledge Management (CIKM 2018)
下载: 论文文档

Multivariate Time Series Imputation with Generative Adversarial Networks
Luo, Yonghong ; Cai, Xiangrui; ZHANG, Ying ; Xu, Jun; Yuan, Xiaojie
Advances in Neural Information Processing Systems 31 (NIPS 2018), 2018.12.2-2018.12.8
下载: 论文文档

Spherical Paragraph Model
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.
下载: 论文文档

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.
下载: 论文文档
链接: 链接

2016
Factorizing Sequential and Historical Purchase Data for Basket Recommendation
Pengfei Wang, Jiafeng Guo, Yanyan Lan, Jun Xu, Xueqi Cheng
Proceedings of the 12th Asia Information Retrieval Societies Conference (AIRS 2016), Beijing, China, pp. 237-248, 2016.

Incorporating Semantic Knowledge into Latent Matching Model in Search
Shuxin Wang, Xin Jiang, Hang Li, Jun Xu, Bin Wang
Proceedings of the 12th Asia Information Retrieval Societies Conference (AIRS 2016), Beijing, China, pp. 29-41, 2016.

Multi-task Representation Learning for Demographic Prediction
Pengfei Wang, Jiafeng Guo, Yanyan Lan, Jun Xu, and Xueqi Cheng
Proceedings of the 37th European Conference on Information Retrieval (ECIR '16), Padua, Italy, pp. 88-99, 2016.

Your Cart tells You: Inferring Demographic Attributes from Purchase Data
Pengfei Wang, Jiafeng Guo, Yanyan Lan, Jun Xu, and Xueqi Cheng
Proceedings of the 9th ACM International Conference on Web Search and Data Mining (WSDM '16), San Francisco, USA, pp. 173-182, 2016.

SPAN: Understanding a Question with its Support Answers
Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, and Xueqi Cheng
Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI '16), Phoenix, Arizona USA, pp. 4250-4251, 2016. poster.

Inside Out: Two Jointly Predictive Models for Word Representations and Phrase Representations
Fei Sun, Jiafeng Guo, Yanyan Lan, Jun Xu, and Xueqi Cheng
Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI '16), Phoenix, Arizona USA, pp. 2821-2827, 2016.

A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations
Shengxian Wan, Yanyan Lan, Jiafeng Guo, Jun Xu, and Xueqi Cheng
Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI '16), Phoenix, Arizona USA, pp. 2835-2841, 2016.

Text Matching as Image Recognition
Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, and Xueqi Cheng
Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI '16), Phoenix, Arizona USA, pp. 2793-2799, 2016.

Sparse Word Embeddings Using l1 Regularized Online Learning
Fei Sun, Jiafeng Guo, Yanyan Lan, Jun Xu, and Xueqi Cheng
Proceedings of the 25th International Joint Conference on Artificial Intelligence. (IJCAI '16), New York, USA, pp. 2915-2921, 2016.

Match-SRNN: Modeling the Recursive Matching Structure with Spatial RNN
Shengxian Wan, Yanyan Lan, Jun Xu, Jiafeng Guo, Liang Pang, Xueqi Cheng
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.
下载: 论文文档
链接: 链接

2013
Learning query and document similarities from click-through bipartite graph with metadata
Wei Wu, Hang Li, and Jun Xu
Proceedings of the sixth ACM international conference on Web search and data mining (WSDM '13), Rome, Italy, pp. 687-696, 2013.

Regularized Latent Semantic Indexing: A New Approach to Large Scale Topic Modeling
Quan Wang, Jun Xu, Hang Li, and Nick Craswell (2013)
ACM Transactions on Information System (TOIS), Vol. 31: No. 1, Article 5, pp 5:1-5:44.
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链接: 链接

2012
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.

How to Make LETOR More Uwseful and Reliable
Tao Qin, Tie-Yan Liu, Jun Xu, and Hang Li
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.
下载: 论文文档

2007
Searching Documents Based on Relevance and Type
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.
下载: 论文文档
链接: 链接

2006
Using SVM to Extract Acronyms from Text
Jun Xu and Ya-lou Huang
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.
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链接: 链接

Cost-sensitive Learning of SVM for Ranking
Jun Xu, Yunbo Cao, Hang Li, and Yalou Huang
Proceedings of the 17th European Conference on Machine Learning (ECML '06), Berlin, Germany, pp. 833-840, 2006.

2005
A Machine Learning Approach to Recognizing Acronyms and Their Expansions
Jun Xu and Ya-lou Huang
Proceedings of the 4th International Conference on Machine Learning and Cybernetics (ICMLC '05), Guangzhou, China, Vol. 4, pp. 2313-2319, 2005.

Ranking Definitions with Supervised Learning Methods
Jun Xu, Yunbo Cao, Hang Li, and Min Zhao
Proceedings of the 14th International World Wide Web Conference (WWW '05), Industrial and Practical Experience Track, Chiba, Japan, pp. 811-819, 2005.

A New Approach to Intranet Search Based on Information Extraction
Hang Li, Yunbo Cao, Jun Xu, Yunhua Hu, Shenjie Li, and Dmitriy Meyerzon
Proceedings of the 14th ACM international conference on Information and knowledge management (CIKM '05), industry track, Bremen, Germany

荣誉奖励

  • 教育部自然科学一等奖(排名第4)
  • 北京市自然科学奖二等奖(排名第2)
  • SIGIR-AP 2023 Best Paper Award
  • WWW 2023 Spotlight论文/Best Paper Nomination
  • CCIR 2022最佳论文奖
  • SIGIR 2019 Test of Time Award Honorable Mention, 2019
  • 中国人民大学优秀科研成果奖(2020)
  • CIKM 2017 Best Full Paper Runner-up, 2017
  • CCF杰出演讲者(2017)
  • AIRS 2010 best paper award, 2010
  • ICMLC 2005 best paper award, 2005
  • 微软学者(2005年)

社会兼职

  • 期刊:ACM TIST(副主编)、JASIST(编委)
  • 会议:Area Chair (SIGIR 2024, NeurIPS, NLPCC 2019, CCL 2018), PC co-chair (CCIR 2023), Publicity co-chair (CIKM 2020), Senior PC (SIGIR, WWW, AAAI, ACML等)
  • CCF高级会员、CCIR常务委员、CIPS青工委委员

contact

电话:--

邮箱:junxu(@)ruc.edu.cn

个人网页:https://ruc-iir-lab.github.io/

办公地址:中国人民大学立德楼1717