简介

徐君，中国人民大学高瓴人工智能学院教授、博士生导师，北京智源人工智能研究院智源学者。曾就职于微软亚洲研究院、华为诺亚方舟实验室（香港）和中国科学院计算技术研究所，于2018年9月加入中国人民大学工作至今。研究领域包括互联网搜索与智能推荐模型和系统，发表论文超过100篇、英文专著2本、中文教科书1本，部分研究成果多次被欧美学者写入信息检索教科书，应用于微软、华为、快手等公司的信息检索产品和开源系统。获ACM SIGIR 2019 Test of Time Award Honorable Mention、ACM SIGIR-AP 2023 Best Paper Award、WWW 2023 Spotlight Paper/Best Paper Nomination、CIKM 2017 Best Full Paper Runner-up、CCIR 2022, AIRS 2010和ICMLC 2005最佳论文奖，获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）。担任学术会议ACM SIGIR和NeurIPS领域主席，是学术期刊ACM TIST副主编和JASIST编委，主持国家重点研发项目/课题和国家自然科学基金面上项目。

教育背景

• 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

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！

科研项目

• 国家重点研发计划：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

学术成果精选

教科书

文继荣，徐君。 “人工智能与Python程序设计（新编21世纪人工智能系列教材）”, 中国人民大学出版社, 2024.

专著

Jun Xu, Xiangnan He and Hang Li. “Deep Learning for Matching in Search and Recommendation”, Now Publishers, 2020. (pdf, link)

（中文译本）徐君, 何向南, 李航. “深度匹配学习：面向搜索与推荐”, 人民邮电出版社, 2023.

Hang Li and Jun Xu. “Semantic Matching in Search”, Now Publishers, 2014. (pdf, link)

论文

2024:

Sunhao Dai, Yuqi Zhou, Liang Pang, Weihao Liu, Xiaolin Hu, Yong Liu, Xiao Zhang, Gang Wang, Jun Xu. Neural Retrievers are Biased Towards LLM-Generated Content. KDD (2024). [PDF]

Haiyuan Zhao, Guohao Cai, Jieming Zhu, Zhenhua Dong, Jun Xu, Ji-Rong Wen. Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time. KDD (2024). [PDF]

Chen Yang, Sunhao Dai, Yupeng Hou, Xin Zhao, Jun Xu, SONG Yang, Hengshu Zhu. Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method. KDD (2024). [PDF]

Jiakai Tang, Sunhao Dai, Zexu Sun, Xu Chen, Jun Xu, Wenhui Yu, Lantao Hu, Peng Jiang, Han Li. Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning. KDD (2024). [PDF]

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

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

Weicong Qin, Zelin Cao, Weijie Yu, Zihua Si, Sirui Chen and Jun Xu. Explicitly Integrating Judgment Prediction with Legal Document Retrieval: A Law-Guided Generative Approach. SIGIR 2024. [PDF]

Sunhao Dai, Changle Qu, Sirui Chen, Xiao Zhang and Jun Xu. ReCODE: Modeling Repeat Consumption with Neural ODE. SIGIR 2024. [PDF]

Zhongxiang Sun, Zihua Si, Xiao Zhang, Xiaoxue Zang, Yang Song, Hongteng Xu and Jun Xu. To Search or to Recommend: Predicting Open-App Motivation with Neural Hawkes Process. SIGIR 2024. [PDF]

Chen Xu, Xiaopeng Ye, Wenjie Wang, Liang Pang, Jun Xu and Tat-Seng Chua. A Taxation Perspective for Fair Re-ranking. SIGIR 2024. [PDF]

Teng Shi, Zihua Si, Jun Xu, Xiao Zhang, Xiaoxue Zang, Kai Zheng, Dewei Leng, Yanan Niu and Yang Song. UniSAR: Modeling User Transition Behaviors between Search and Recommendation. SIGIR 2024. [PDF]

Shicheng Xu, Danyang Hou, Liang Pang, Jingcheng Deng, Jun Xu, Huawei Shen and Xueqi Cheng. Invisible Relevance Bias: Text-Image Retrieval Models Prefer AI-Generated Images. SIGIR 2024. [PDF]

Changshuo Zhang, Sirui Chen, Xiao Zhang, Sunhao Dai, Weijie Yu, Jun Xu. Reinforcing Long-Term Performance in Recommender Systems with User-Oriented Exploration Policy. SIGIR 2024. [PDF]

Jianwen Yang, Xiao Zhang, Jun Xu. Smooth Start: A Unified Approach for gradual transition from cold to old in Recommender Systems. ICASSP 2024. [PDF]

ZhongXiang Sun, Kepu Zhang, Weijie Yu, Haoyu Wang and Jun Xu. Logic Rules as Explanations for Legal Case Retrieval. COLING 2024. [PDF]

Shicheng Xu, Liang Pang, Jun Xu, Huawei Shen, Xueqi Cheng. List-aware Reranking-Truncation Joint Model for Search and Retrieval-augmented Generation. WWW 2024. [PDF]

Chen Xu, Jun Xu, Yiming Ding, Xiao Zhang, Qi Qi. FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval. WWW 2024. [PDF]

2023:

Xiao Zhang, Ninglu Shao, Zihua Si, Jun Xu, Wenhan Wang, Hanjing Su, Ji-Rong Wen. Reward Imputation with Sketching for Contextual Batched Bandits. NeurIPS 2023. [PDF]

Zhongxiang Sun, Weijie Yu, Zihua Si, Jun Xu, Zhenhua Dong, Xu Chen, Hongteng Xu, Ji-Rong Wen. Explainable Legal Case Matching via Graph Optimal Transport. TKDE. [PDF]

Sirui Chen, Xiao Zhang, Xu Chen, Zhiyu Li, Yuan Wang, Quan Lin, and Jun Xu. Reinforcement Re-ranking with 2D Grid-based Recommendation Panels. SIGIR-AP 23. [PDF]

Haiyuan Zhao, Jun Xu, Xiao Zhang, Guohao Cai, Zhenhua Dong, Ji-Rong Wen. Unbiased Top-$k$ Learning to Rank with Causal Likelihood Decomposition. SIGIR-AP 23. [PDF]

Chenglei Shen, Xiao Zhang, Wei Wei, Jun Xu. HyperBandit: Contextual Bandit with Hypernewtork for Time-Varying User Preferences in Streaming Recommendation. CIKM 2023. [PDF]

Zhongxiang Sun, Zihua Si, Xiaoxue Zang, Dewei Leng, Yanan Niu, Yang Song, Xiao Zhang, Jun Xu. KuaiSAR: A Unified Search And Recommendation Dataset. CIKM 2023. [PDF]

Sunhao Dai, Yuqi Zhou, Jun Xu, Ji-Rong Wen. Dually Enhanced Delayed Feedback Modeling for Streaming Conversion Rate Prediction. CIKM 2023. [PDF]

Sunhao Dai, Ninglu Shao, Haiyuan Zhao, Weijie Yu, Zihua Si, Chen Xu, Zhongxiang Sun, Xiao Zhang, Jun Xu. Uncovering ChatGPT’s Capabilities in Recommender Systems. RecSys 2023. [PDF]

Chen Xu, Jun Xu, Zhenhua Dong, Ji-Rong, Wen. Syntactic-Informed Graph Networks for Sentence Matching. TOIS. [PDF]

Haiyuan Zhao, Lei Zhang, Jun Xu, Guohao Cai, Zhenhua Dong and Ji-Rong Wen. Uncovering User Interest from Biased and Noised Watch Time in Video Recommendation. RecSys 2023. [PDF]

Sirui Chen, Yuan Wang, Zijing Wen, Zhiyu Li, ChangShuo Zhang, Xiao Zhang, Lin Quan, Cheng Zhu, Jun Xu. Controllable Multi-Objective Re-ranking with Policy Hypernetworks. KDD 2023 (ADS track). [PDF]

Ruiqi Zhao, Lei Zhang, Shengyu Zhu, Zitong Lu, Zhenhua Dong, Chaoliang Zhang, Jun Xu, Zhi Geng, Yangbo He. Conditional Counterfactual Causal Effect for Individual Attribution. UAI 2023. [PDF]

薄琳，庞亮，张朝亮，王钊伟，董振华，徐君，文继荣. ACRank: 在神经排序模型中引入检索公理知识. 计算机学报. [PDF]

Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Xiaoxue Zang, Yang Song, Kun Gai and Ji-Rong Wen. When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation. SIGIR 2023. [PDF]

Zhongxiang Sun, Jun Xu, Xiao Zhang, Zhenhua Dong, Ji-Rong Wen. Law Article-Enhanced Legal Case Matching: a Causal Learning Approach. SIGIR 2023. [PDF]

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

Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Yang Song, Xiaoxue Zang, Ji-Rong Wen. Enhancing Recommendation with Search Data in a Causal Learning Manner. TOIS vol.41. [PDF]

Chen Xu, Sirui Chen, Jun Xu, Weiran Shen, Xiao Zhang, Gang Wang, Zhenghua Dong. P-MMF: Provider Max-min Fairness Re-ranking in Recommender System. WWW 2023 (Splotlight - Best Paper Nomination). [PDF]

Chen Xu, Sirui Chen, Jun Xu, Weiran Shen, Xiao Zhang, Gang Wang, Zhenghua Dong. P-MMF: Provider Max-min Fairness Re-ranking in Recommender System. WWW 2023. [PDF]

2022:

Xiao Zhang, Sunhao Dai, Jun Xu, Zhenhua Dong, Quanyu Dai, Ji-Rong Wen. Counteracting user attention bias in music streaming recommendation via reward modification. KDD 2022. [PDF]

Weijie Yu, Zhongxiang Sun, Jun Xu, Zhenhua Dong, Xu Chen, Hongteng Xu, Ji-Rong Wen. Explainable Legal Case Matching via Inverse Optimal Transport-based Rationale Extraction. SIGIR 2022. [PDF]

Zihua Si, Xueran Han, Xiao Zhang, Jun Xu, Yue Yin, Yang Song, Ji-Rong Wen. A Model-Agnostic Causal Learning Framework for Recommendation using Search Data. WWW 2022. [PDF]

Weijie Yu; Chen Xu; Jun Xu; Liang Pang; Ji-Rong Wen. Distribution Distance Regularized Sequence Representation for Text Matching in Asymmetrical Domains. TASLP vol.30. [PDF]

Weijie Yu, Liang Pang, Jun Xu, Bing Su, Zhenhua Dong, Ji-Rong Wen. Optimal Partial Transport Based Sentence Selection for Long-form Document Matching. COLING 2022. [PDF]

Chen Xu, Jun Xu, Zhenhua Dong, Ji-Rong Wen. Semantic Sentence Matching via Interacting Syntax Graphs. COLING 2022. [PDF]

Chen Xu, Jun Xu, Xu Chen, Zhenghua Dong, Ji-Rong Wen. Dually Enhanced Propensity Score Estimation in Sequential Recommendation. CIKM 2022. [PDF]

Kerui Xu, Jun Xu, Sheng Gao, Si Li, Jun Guo, Ji-Rong Wen. A Tag-Based Post-Hoc Framework for Explainable Conversational Recommendation. ICTIR 2022. [PDF]

Haiyuan Zhao, Jun Xu, Xiao Zhang, Guohao Cai, Zhenghua Dong, Ji-rong Wen. Separating Examination and Trust Bias from Click Predictions for Unbiased Relevance Ranking. WSDM 2023. [PDF]

Haonan Jia, Xiao Zhang, Jun Xu, Wei Zeng, Hao Jiang,Xiaohui Yan. Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient. ICTIR 2022. [PDF]

2021:

Xiao Zhang, Shizhong Liao, Jun Xu, Ji-Rong Wen. Regret Bounds for Online Kernel Selection in Continuous Kernel Space. AAAI 2021. [PDF]

Xiao Zhang, Haonan Jia, Hanjing Su, Wenhan Wang, Jun Xu, Ji-Rong Wen. Counterfactual Reward Modification for Streaming Recommendation with Delayed Feedback. SIGIR 2021. [PDF]

Kerui Xu, Jingxuan Yang, Jun Xu, Sheng Gao, Jun Guo, Ji-Rong Wen. Adapting User Preference to Online Feedback in Multi-round Conversational Recommendation. WSDM 2021. [PDF]

Jingxuan Yang, Kerui Xu, Jun Xu, Si Li, Sheng Gao, Jun Guo, Nianwen Xue, Ji-Rong Wen. A Joint Model for Dropped Pronoun Recovery and Conversational Discourse Parsing in Chinese Conversational Speech. ACL 2021. [PDF]

Jing Yao, Zhicheng Dou, Jun Xu, Ji-Rong Wen. RLPS: A reinforcement learning–based framework for personalized search. TOIS 2021. [PDF]