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). [Just Accepted]
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). [Just Accepted]
Chen Yang, Sunhao Dai, Yupeng Hou, Xin Zhao, Jun Xu, SONG Yang, Hengshu Zhu. Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method. KDD (2024). [Just Accepted]
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). [Just Accepted]
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). [Just Accepted]
ZhongXiang Sun, Kepu Zhang, Haoyu Wang, Xiao Zhang, Jun Xu. Effective In-Context Example Selection through Data Compression. ACL Findings (2024). [Just Accepted]
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. [Just Accepted]
Sunhao Dai, Changle Qu, Sirui Chen, Xiao Zhang and Jun Xu. ReCODE: Modeling Repeat Consumption with Neural ODE. SIGIR 2024. [Just Accepted]
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. [Just Accepted]
Chen Xu, Xiaopeng Ye, Wenjie Wang, Liang Pang, Jun Xu and Tat-Seng Chua. A Taxation Perspective for Fair Re-ranking. SIGIR 2024. [Just Accepted]
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. [Just Accepted]
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. [Just Accepted]
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. [Just Accepted]
Jianwen Yang, Xiao Zhang, Jun Xu. Smooth Start: A Unified Approach for gradual transition from cold to old in Recommender Systems. ICASSP 2024. [Just Accepted]
ZhongXiang Sun, Kepu Zhang, Weijie Yu, Haoyu Wang and Jun Xu. Logic Rules as Explanations for Legal Case Retrieval. COLING 2024. [Just Accepted]
Shicheng Xu, Liang Pang, Jun Xu, Huawei Shen, Xueqi Cheng. List-aware Reranking-Truncation Joint Model for Search and Retrieval-augmented Generation. WWW 2024. [Just Accepted]
Chen Xu, Jun Xu, Yiming Ding, Xiao Zhang, Qi Qi. FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval. WWW 2024. [Just Accepted]
Sunhao Dai, Ninglu Shao, Jieming Zhu, Xiao Zhang, Zhenhua Dong, Jun Xu, Quanyu Dai, Ji-Rong Wen. Modeling User Attention in Music Recommendation. ICDE 2024. [Just Accepted]
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]
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]
2020：
Weijie Yu, Chen Xu, Jun Xu, Liang Pang, Xiaopeng Gao, Xiaozhao Wang, Ji-Rong Wen. Wasserstein Distance Regularized Sequence Representation for Text Matching in Asymmetrical Domains. EMNLP 2020 main conference. [PDF]
Jun Xu, Zeng Wei, Long Xia, Yanyan Lan, Dawei Yin, Xueqi Cheng, Ji-Rong Wen. Reinforcement Learning to Rank with Pairwise Policy Gradient. SIGIR 2020. [PDF]
Liang Pang, Jun Xu, Qingyao Ai, Yanyan Lan, Xueqi Cheng, Jirong Wen. SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval. SIGIR 2020. [PDF]
Jingxuan Yang, Kerui Xu, Jun Xu, Si Li, Sheng GAO, Jun Guo, Ji-Rong Wen, Nianwen Xue. Transformer-GCRF: Recovering Chinese Dropped Pronouns with General Conditional Random Fields. EMNLP 2020. [PDF]
Jing Yao, Zhicheng Dou, Jun Xu, Ji-Rong Wen. RLPer: A Reinforcement Learning Model for Personalized Search. WWW 2020. [PDF]
2019：
Jun Xu, Wei Zeng, Yanyan Lan, Jiafeng Guo, Xueqi Cheng. Modeling the Parameter Interactions in Ranking SVM with Low-Rank Approximation. TKDE 2019, 31(6). [PDF]
Yadi Lao, Jun Xu, Sheng Gao, Jun Guo, Ji-Rong Wen. Name Entity Recognition with Policy-Value Networks. SIGIR 2019. [PDF]
Zhaohui Li, Yue Feng, Jun Xu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng. Teaching Machines to Extract Main Content for Machine Reading Comprehension. AAAI 2019. [PDF]
Yonghong Luo, Xiangrui Cai, Ying Zhang, Jun Xu, Xiaojie Yuan. Multivariate Time Series Imputation with Generative Adversarial Networks. NIPS 2018. [PDF]
Shuqi Lu, Zhicheng Dou, Jun Xu, Jian-Yun Nie, Ji-Rong Wen. PSGAN: A Minimax Game for Personalized Search with Limited and Noisy Click Data. SIGIR 2019. [PDF]
Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, Lixin Su, Xueqi Cheng. HAS-QA: Hierarchical Answer Spans Model for Open-Domain Question Answering. AAAI 2019. [PDF]
Jianing Li, Yanyan Lan, Jiafeng Guo, Jun Xu, Xueqi Cheng. Differentiated Distribution Recovery for Neural Text Generation. AAAI 2019. [PDF]
学术报告
“Beyond Probability Ranking Principle: Modeling the Dependencies among Documents”
Liang Pang, Qingyao Ai, Jun Xu ,
tutorial at SIGIR 2021.
(Tutorial Slides and Presentations).
“Beyond Probability Ranking Principle: Modeling the Dependencies among Documents”
Liang Pang, Qingyao Ai, Jun Xu ,
tutorial at WSDM 2021.
(Tutorial Slides and Presentations).
“基于因果分析的搜索纠偏方法”
徐君、张骁 ,
第二十七届全国信息检索学术会议（CCIR2021）教学报告.
(slides).
“Deep Learning for Matching in Search and Recommendation”
Jun Xu, Xiangnan He, Hang Li ,
tutorial at SIGIR 2018.
(slides, link).
“Deep Learning for Matching in Search and Recommendation”
Jun Xu, Xiangnan He, Hang Li ,
tutorial at WWW 2018.
(slides, link).
“Deep Learning for Semantic Matching in Search”
Jun Xu ,
tutorial at the NLPCC 2017 & ADL 86, 2017.
(slides).
“EasyML: Ease the Process of Machine Learning with Data Flow”
Jun Xu ,
invited talk at the workshop on AI Systems at Symposium on Operating Systems Principles (SOSP), 2017.
(slides, link).
“Deep Approaches to Semantic Text Matching”
Jun Xu ,
keynote speech at the First SIGIR Workshop on Knowledge Graphs and Semantics for Text Retrieval and Analysis, 2017.
(slides).
“Reinforcement Learning to Rank with Markov Decision Process”
Jun Xu ,
invited talk at CCF@U (Dalian and Wuhang), 2017.
(slides).
“Deep Approaches to Semantic Matching for Text”
Jun Xu ,
tutorial at the 22nd China Conference on Information Retrieval, CCIR 2016.
(slides).
“Learning to rank revisited: our progresses in new algorithms and tasks”
Jun Xu ,
invited talk at the 4th China-Australia Database Workshop, 2015.
(slides).
“Learning to rank, from relevance to relational”
Jun Xu ,
tutorial at the 21st China Conference on Information Retrieval, CCIR 2015.
(slides).
“Learning for Search Result Diversification”
Jun Xu ,
tutorial at CCF YOCSEF Tianjin, 2015.
(slides).
“Post Processing of Ranking in Search”
Jun Xu ,
invited talk at WSDM 2015 workshop on Vertical Search Relevance, 2015.
(slides).
“Semantic matching in search”
Jun Xu ,
tutorial at NLPCC 2014 & ADL 52, 2014.
(slides).
“Beyond Bag-of-words: Machine Learning for Matching”
Hang Li, Jun Xu ,
invited talk at SIGIR 2013 workshop on Internet Advertising: Theory and Practice (IATP), 2013.
“Beyond Bag-of-Words: Machine Learning for Query-Document Matching”
Jun Xu ,
tutorial at SIGIR 2012.
(slides).
“Machine Learning for Query-Document Matching in Search”
Jun Xu ,
tutorial at WSDM 2012.
“Machine Learning for Query-Document Matching in Search”
Jun Xu ,
tutorial at WWW 2012.
“A Kernel Approach to Matching of Query and Document in Search”
Jun Xu ,
invited talk at ACLCLP IR Workshop, National Taiwan University, Taipei, 2010.