Xin Xin's Homepage

News

April 2023
Three full papers about multi-behavior recommendation, RL-based recommendation, and sequential recommendation were accepted by SIGIR'23.

Feberary 2023
One full paper about sequential recommendation was accepted by WWW'23.

October 2022
One full paper about conversational recommendation was accepted by WSDM'23.

July 2022
One paper about recommendation privacy was accepted by TOIS.

April 2022
One resource paper about medical conversation was accepted by SIGIR'22 resource track.

March 2022
Two full papers about reinforcement learning for recommendation, and conversational recommendation were accepted by SIGIR'22.

March 2022
One paper about graph-based social recommendation was accepted by TKDE.

Jan 2022
One full paper about denoising recommender systems was accepted by WWW'22!

Oct 2021
Two full papers about reinforcement learning for recommender systems were accepted by WSDM'22!

Sep 2021
One full paper about pre-training of recommender systems was accepted by ICDM'21!

August 2021
I have joined the School of Computing Science and Technology of Shandong University as a tenure-track assistant professor!

August 2021
One full paper about sequential recommendation was accepted by CIKM'21!

April 2021
Two full paper about recommendation biasing and graph learning debiasing were accepted by SIGIR'21!

April 2021
I have been awarded the PhD degree in Computing Science!

March 2021
I have successfully passed my PhD viva defense and a PhD degree will be awarded soon!

October 2020
One full paper about graph learning for explainable recommendation was accepted by WSDM'21. Collaborated with Hao Chen in SJTU.

July 2020
One full paper about graph learning for tag recommendation was accepted by CIKM'20. Collaborated with Bo Chen in SJTU.

April 2020
One full paper about reinforcement learning for recommendation was accepted by SIGIR'20. Collaborated with Dr.Alexandros Karatzoglou in Google.

April 2019
One full paper about relational modeling for item-based collaborative filtering was accepted by SIGIR'19. Collaborated with Dr.Xiangnan He.

April 2019
One full paper about CNN for improved factorization machines was accepted by IJCAI'19. Collaborated with Bo Chen in SJTU.

May 2018
One full paper about fast batch gradient descent was accepted by UAI'18.

April 2018
A full paper about word embedding was accepted by ACL'18.

Xin Xin (辛鑫)

Assistant Professor
(Associate Researcher)
Information Retrieval Lab
School of Computer Science and Technology
Shandong University, China

Email: xinxin@sdu.edu.cn
Room 414-1, N3 Floor, 72 Binhai Road, Qingdao

Xin Xin is now a tenure-track assistant professor (Associate Researcher) in the School of Computer Science and Technology of Shandong University, as a member of the Information Retrieval Lab. Before that, he got his PhD degree in computing science from University of Glasgow, under the supervision of Prof. Joemon Jose. Formerly, he got his master degree from School of Software Engineering in SJTU (上海交通大学) and his bachelor degree from XJTU (西安交通大学). His research interests span recommender systems, reinforcement learning, graph learning, causual inference for recommendation and NLP. His work appeared in sereval top-tier ML & IR conferences including SIGIR, WSDM, CIKM, IJCAI, ACL and UAI. His PhD is supported by Chinese Scholarship Council.

I'm looking for self-motivated (I won't push students while a good student should push me) master students. If you are interested in recommendation, reinforcement learning, and related fields, please drop me your CV (recruiting numbers depends on my funding). PS: Competition could be intense. Applicants are encouraged to have good communication ability (both in Chinese and English) since we could have densely connections with top-100 oversea universites and frequent presentations on international (CCF A/B) conferences. A good researcher should always be happy to share thoughts with peers.

Selected Publications [Google Scholar ] [Core Rank ]

pdf	Improving Implicit Feedback-Based Recommendation through Multi-Behavior Alignment Xin Xin, Xiangyuan Liu, Hanbing Wang, Pengjie Ren, Zhumin Chen, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon Jose, Maarten de Rijke and Zhaochun Ren SIGIR 2023 (CORE rank A*)

pdf	Contrastive State Augmentations for Reinforcement Learning-Based Recommender Systems Zhaochun Ren, Na Huang, Yidan Wang, Pengjie Ren, Jun Ma, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon Jose and Xin Xin SIGIR 2023 (CORE rank A*)(corresponding author)

pdf	A Generic Learning Framework for Sequential Recommendation with Distribution Shifts Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen and Xiang Wang SIGIR 2023 (CORE rank A*)

pdf	A Self-Correcting Sequential Recommender Yujie Lin, Chenyang Wang, Zhumin Chen, Zhaochun Ren, Xin Xin, Qiang Yan, Maarten de Rijke, Xiuzhen Cheng, Pengjie Ren WWW 2023 (CORE rank A*)

pdf	Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation Xiaoyu Zhang，Xin Xin, Dongdong Li, Wenxuan Liu, Pengjie Ren, Zhumin Chen, Jun Ma, Zhaochun Ren WSDM 2023 (CORE rank A*)

pdf	On the User Behavior Leakage from Recommender Exposure Xin Xin, Jiyuan Yang, Hanbing Wang, Jun Ma, Pengjie Ren, Hengliang Luo, Xinlei Shi, Zhumin Chen, Zhaochun Ren TOIS (CCF A)

pdf	Rethinking Reinforcement Learning for Recommendation: A Prompt Perspective Xin Xin, Tiago Pimentel, Alexandros Karatzoglou, Pengjie Ren, Konstantina Christakopoulou, Zhaochun Ren SIGIR 2022 (CORE rank A*)

pdf	Variational Reasoning about User Preferences for Conversational Recommendation Zhaochun Ren, Zhi Tian, Dongdong Li, Pengjie Ren, Liu Yang, Xin Xin, Huasheng Liang, Maarten de Rijke, Zhumin Chen SIGIR 2022 (CORE rank A*)

pdf	ReMeDi: Resources for Multi-domain, Multi-service, Medical Dialogues Guojun Yan, Jiahuan Pei, Pengjie Ren, Zhaochun Ren, Xin Xin, Huasheng Liang, Maarten de Rijke, Zhumin Chen SIGIR 2022 (CORE rank A*)

pdf	GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation Chen Jiajia, Xin Xin , Xianfeng Liang, Xiangnan He, Jun Liu TKDE

pdf	Learning Robust Recommenders through Cross-Model Agreement Yu Wang, Xin Xin , Zaiqiao Meng, Xiangnan He, Joemon Jose, Fuli Feng WWW 2022 (CORE rank A) (*corresponding author) (Codes avaliable soon)

pdf	Supervised Advantage Actor-Critic for Recommender Systems Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M Jose WSDM 2022 (CORE rank A*)

pdf	Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning Dusan Stamenkovic, Alexandros Karatzoglou, Ioannis Arapakis, Xin Xin, Kleomenis Katevas WSDM 2022 (CORE rank A*)

pdf	Learning Transferable User Representations with Sequential Behaviors via Contrastive Pre-training Mingyue Cheng, Fajie Yuan, Qi Liu, Xin Xin , Enhong Chen ICDM 2021 (CORE rank A*) (Codes avaliable soon)

pdf	Extracting Attentive Social Temporal Excitation for Sequential Recommendation Yunzhe Li, Yue Ding, Bo Chen, Xin Xin , Yule Wang, Yuxiang Shi, Ruiming Tang and Dong Wang CIKM 2021 (CORE rank A)

pdf	Should graph convolution trust neighbors? a simple causal inference method Fuli Feng, Weiran Huang, Xiangnan He, Xin Xin, Qifan Wang, Tat-Seng Chua SIGIR 2021 (CORE rank A*)

pdf	AutoDebias: Learning to Debias for Recommendation Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, Keping Yang SIGIR 2021 (CORE rank A*)

pdf	Decomposed Collaborative Filtering: Modeling Explicit and Implicit Factors For Recommender Systems Hao Chen, Xin Xin, Dong Wang, Yue Ding WSDM 2021 (Accept rate: 18.6%) (CORE rank A*) Codes

pdf	TGCN: Tag Graph Convolutional Network for Tag-Aware Recommendation Bo Chen, Wei Guo, Ruiming Tang, Xin Xin, Yue Ding, Xiuqiang He, Dong Wang CIKM 2020 (Accept rate: 21%) (CORE rank A)

pdf	Self-Supervised Reinforcement Learning for Recommender Systems Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M Jose SIGIR 2020 (Accept rate: 26%) (CORE rank A*) Codes

pdf	Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation Xin Xin, Xiangnan He, Yongfeng Zhang, Yongdong Zhang, Joemon Jose SIGIR 2019 (Accept rate: 20%) (CORE rank A*) Codes

pdf	CFM: Convolutional Factorization Machines for Context-Aware Recommendation Xin Xin, Bo Chen (co-first author), Xiangnan He, Dong Wang, Yue Ding and Joemon M. Jose IJCAI 2019 (Accept rate: 17.9%) (CORE rank A*) Codes

pdf	fBGD: Learning Embeddings From Positive Unlabeled Data with BGD Fajie Yuan, Xin Xin, Xiangnan He, Guibing Guo, Weinan Zhang, T. Chua, J. Jose UAI 2018. (Accept rate: 30%)(CORE rank A*) Codes

pdf	Batch IS NOT Heavy: Learning Word Representations From All Samples Xin Xin, Fajie Yuan (co-first authors), Xiangnan He, Joemon M Jose ACL 2018.(Accept rate: 24.8%)(CORE rank A*) Codes

Some of code repos have changed to new github username xinxin-me.