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Xin Xin 0003
Person information
- unicode name: 辛鑫
- affiliation: Shandong University, Information Retrieval Lab, School of Computer Science and Technology, China
- affiliation (PhD 2021): University of Glasgow, School of Computing Science, UK
- affiliation: Shanghai Jiao Tong University, School of Software, School of Electronic Information and Electrical Engineering, China
Other persons with the same name
- Xin Xin — disambiguation page
- Xin Xin 0001 — Beijing Institute of Technology, Beijing School of Computer Science and Technology, China
- Xin Xin 0002 — Chinese University of Hong Kong, Department of Computer Science and Engineering, Hong Kong
- Xin Xin 0004 — Okayama Prefectural University, Faculty of Computer Science and Systems Engineering, Japan
- Xin Xin 0005 — Xi'an University of Posts and Telecommunications, School of Electronics Engineering, China
- Xin Xin 0006 — Beijing Normal University, Faculty of Psychology, China
- Xin Xin 0007 — University of Glasgow, School of Computing Science, UK (and 1 more)
- Xin Xin 0008 — University of Central Florida, FL, USA (and 2 more)
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2020 – today
- 2024
- [j9]Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He:
How graph convolutions amplify popularity bias for recommendation? Frontiers Comput. Sci. 18(5): 185603 (2024) - [j8]Chaoyu Shi, Pengjie Ren, Dongjie Fu, Xin Xin, Shansong Yang, Fei Cai, Zhaochun Ren, Zhumin Chen:
Diversifying Sequential Recommendation with Retrospective and Prospective Transformers. ACM Trans. Inf. Syst. 42(5): 132:1-132:37 (2024) - [c37]Shen Gao, Zhengliang Shi, Minghang Zhu, Bowen Fang, Xin Xin, Pengjie Ren, Zhumin Chen, Jun Ma, Zhaochun Ren:
Confucius: Iterative Tool Learning from Introspection Feedback by Easy-to-Difficult Curriculum. AAAI 2024: 18030-18038 - [c36]Jitai Hao, Weiwei Sun, Xin Xin, Qi Meng, Zhumin Chen, Pengjie Ren, Zhaochun Ren:
MEFT: Memory-Efficient Fine-Tuning through Sparse Adapter. ACL (1) 2024: 2375-2388 - [c35]Zaiqiao Meng, Shangsong Liang, Xin Xin, Gianluca Moro, Evangelos Kanoulas, Emine Yilmaz:
KEIR @ ECIR 2024: The First Workshop on Knowledge-Enhanced Information Retrieval. ECIR (5) 2024: 398-402 - [c34]Xiaoyu Zhang, Ruobing Xie, Yougang Lyu, Xin Xin, Pengjie Ren, Mingfei Liang, Bo Zhang, Zhanhui Kang, Maarten de Rijke, Zhaochun Ren:
Towards Empathetic Conversational Recommender Systems. RecSys 2024: 84-93 - [c33]Junchen Fu, Xuri Ge, Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Jie Wang, Joemon M. Jose:
IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT. SIGIR 2024: 687-697 - [c32]Qingpeng Cai, Xiangyu Zhao, Ling Pan, Xin Xin, Jin Huang, Weinan Zhang, Li Zhao, Dawei Yin, Grace Hui Yang:
AgentIR: 1st Workshop on Agent-based Information Retrieval. SIGIR 2024: 3025-3028 - [c31]Xin Xin, Liu Yang, Ziqi Zhao, Pengjie Ren, Zhumin Chen, Jun Ma, Zhaochun Ren:
On the Effectiveness of Unlearning in Session-Based Recommendation. WSDM 2024: 855-863 - [c30]Jiyuan Yang, Yue Ding, Yidan Wang, Pengjie Ren, Zhumin Chen, Fei Cai, Jun Ma, Rui Zhang, Zhaochun Ren, Xin Xin:
Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure. WSDM 2024: 882-890 - [i33]Jiyuan Yang, Yuanzi Li, Jingyu Zhao, Hanbing Wang, Muyang Ma, Jun Ma, Zhaochun Ren, Mengqi Zhang, Xin Xin, Zhumin Chen, Pengjie Ren:
Uncovering Selective State Space Model's Capabilities in Lifelong Sequential Recommendation. CoRR abs/2403.16371 (2024) - [i32]Yidan Wang, Zhaochun Ren, Weiwei Sun, Jiyuan Yang, Zhixiang Liang, Xin Chen, Ruobing Xie, Su Yan, Xu Zhang, Pengjie Ren, Zhumin Chen, Xin Xin:
Enhanced Generative Recommendation via Content and Collaboration Integration. CoRR abs/2403.18480 (2024) - [i31]Junchen Fu, Xuri Ge, Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Jie Wang, Joemon M. Jose:
IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT. CoRR abs/2404.02059 (2024) - [i30]Ziqi Zhao, Zhaochun Ren, Liu Yang, Fajie Yuan, Pengjie Ren, Zhumin Chen, Jun Ma, Xin Xin:
Offline Trajectory Generalization for Offline Reinforcement Learning. CoRR abs/2404.10393 (2024) - [i29]Jitai Hao, Weiwei Sun, Xin Xin, Qi Meng, Zhumin Chen, Pengjie Ren, Zhaochun Ren:
MEFT: Memory-Efficient Fine-Tuning through Sparse Adapter. CoRR abs/2406.04984 (2024) - [i28]Yue Ding, Yanbiao Ji, Xun Cai, Xin Xin, Xiaofeng Gao, Hongtao Lu:
Towards Personalized Federated Multi-scenario Multi-task Recommendation. CoRR abs/2406.18938 (2024) - [i27]Zhiwei Xu, Hangyu Mao, Nianmin Zhang, Xin Xin, Pengjie Ren, Dapeng Li, Bin Zhang, Guoliang Fan, Zhumin Chen, Changwei Wang, Jiangjin Yin:
Beyond Local Views: Global State Inference with Diffusion Models for Cooperative Multi-Agent Reinforcement Learning. CoRR abs/2408.09501 (2024) - [i26]Xiaoyu Zhang, Ruobing Xie, Yougang Lyu, Xin Xin, Pengjie Ren, Mingfei Liang, Bo Zhang, Zhanhui Kang, Maarten de Rijke, Zhaochun Ren:
Towards Empathetic Conversational Recommender Systems. CoRR abs/2409.10527 (2024) - 2023
- [j7]Qingyao Ai, Ting Bai, Zhao Cao, Yi Chang, Jiawei Chen, Zhumin Chen, Zhiyong Cheng, Shoubin Dong, Zhicheng Dou, Fuli Feng, Shen Gao, Jiafeng Guo, Xiangnan He, Yanyan Lan, Chenliang Li, Yiqun Liu, Ziyu Lyu, Weizhi Ma, Jun Ma, Zhaochun Ren, Pengjie Ren, Zhiqiang Wang, Mingwen Wang, Ji-Rong Wen, Le Wu, Xin Xin, Jun Xu, Dawei Yin, Peng Zhang, Fan Zhang, Weinan Zhang, Min Zhang, Xiaofei Zhu:
Information Retrieval meets Large Language Models: A strategic report from Chinese IR community. AI Open 4: 80-90 (2023) - [j6]Jiajia Chen, Xin Xin, Xianfeng Liang, Xiangnan He, Jun Liu:
GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation. IEEE Trans. Knowl. Data Eng. 35(5): 4813-4824 (2023) - [j5]Xin Xin, Jiyuan Yang, Hanbing Wang, Jun Ma, Pengjie Ren, Hengliang Luo, Xinlei Shi, Zhumin Chen, Zhaochun Ren:
On the User Behavior Leakage from Recommender System Exposure. ACM Trans. Inf. Syst. 41(3): 57:1-57:25 (2023) - [c29]Xin Xin, Xiangyu Zhao, Jin Huang, Weinan Zhang, Li Zhao, Dawei Yin, Grace Hui Yang:
DRL4IR: 4th Workshop on Deep Reinforcement Learning for Information Retrieval. CIKM 2023: 5304-5307 - [c28]Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen, Xiang Wang:
A Generic Learning Framework for Sequential Recommendation with Distribution Shifts. SIGIR 2023: 331-340 - [c27]Zhaochun Ren, Na Huang, Yidan Wang, Pengjie Ren, Jun Ma, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon M. Jose, Xin Xin:
Contrastive State Augmentations for Reinforcement Learning-Based Recommender Systems. SIGIR 2023: 922-931 - [c26]Xin Xin, Xiangyuan Liu, Hanbing Wang, Pengjie Ren, Zhumin Chen, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon M. Jose, Maarten de Rijke, Zhaochun Ren:
Improving Implicit Feedback-Based Recommendation through Multi-Behavior Alignment. SIGIR 2023: 932-941 - [c25]Xiaoyu Zhang, Xin Xin, Dongdong Li, Wenxuan Liu, Pengjie Ren, Zhumin Chen, Jun Ma, Zhaochun Ren:
Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation. WSDM 2023: 231-239 - [c24]Yujie Lin, Chenyang Wang, Zhumin Chen, Zhaochun Ren, Xin Xin, Qiang Yan, Maarten de Rijke, Xiuzhen Cheng, Pengjie Ren:
A Self-Correcting Sequential Recommender. WWW 2023: 1283-1293 - [i25]Yujie Lin, Chenyang Wang, Zhumin Chen, Zhaochun Ren, Xin Xin, Qiang Yan, Maarten de Rijke, Xiuzhen Cheng, Pengjie Ren:
A Self-Correcting Sequential Recommender. CoRR abs/2303.02297 (2023) - [i24]Xin Xin, Xiangyuan Liu, Hanbing Wang, Pengjie Ren, Zhumin Chen, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon M. Jose, Maarten de Rijke, Zhaochun Ren:
Improving Implicit Feedback-Based Recommendation through Multi-Behavior Alignment. CoRR abs/2305.05585 (2023) - [i23]Zhaochun Ren, Na Huang, Yidan Wang, Pengjie Ren, Jun Ma, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon M. Jose, Xin Xin:
Contrastive State Augmentations for Reinforcement Learning-Based Recommender Systems. CoRR abs/2305.11081 (2023) - [i22]Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He:
How Graph Convolutions Amplify Popularity Bias for Recommendation? CoRR abs/2305.14886 (2023) - [i21]Qingyao Ai, Ting Bai, Zhao Cao, Yi Chang, Jiawei Chen, Zhumin Chen, Zhiyong Cheng, Shoubin Dong, Zhicheng Dou, Fuli Feng, Shen Gao, Jiafeng Guo, Xiangnan He, Yanyan Lan, Chenliang Li, Yiqun Liu, Ziyu Lyu, Weizhi Ma, Jun Ma, Zhaochun Ren, Pengjie Ren, Zhiqiang Wang, Mingwen Wang, Ji-Rong Wen, Le Wu, Xin Xin, Jun Xu, Dawei Yin, Peng Zhang, Fan Zhang, Weinan Zhang, Min Zhang, Xiaofei Zhu:
Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community. CoRR abs/2307.09751 (2023) - [i20]Yu Wang, Xin Xin, Zaiqiao Meng, Xiangnan He, Joemon M. Jose, Fuli Feng:
Label Denoising through Cross-Model Agreement. CoRR abs/2308.13976 (2023) - [i19]Shen Gao, Zhengliang Shi, Minghang Zhu, Bowen Fang, Xin Xin, Pengjie Ren, Zhumin Chen, Jun Ma:
Confucius: Iterative Tool Learning from Introspection Feedback by Easy-to-Difficult Curriculum. CoRR abs/2308.14034 (2023) - [i18]Shiguang Wu, Xin Xin, Pengjie Ren, Zhumin Chen, Jun Ma, Maarten de Rijke, Zhaochun Ren:
Learning Robust Sequential Recommenders through Confident Soft Labels. CoRR abs/2311.02446 (2023) - [i17]Jiyuan Yang, Yue Ding, Yidan Wang, Pengjie Ren, Zhumin Chen, Fei Cai, Jun Ma, Rui Zhang, Zhaochun Ren, Xin Xin:
Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure. CoRR abs/2312.07036 (2023) - [i16]Xin Xin, Liu Yang, Ziqi Zhao, Pengjie Ren, Zhumin Chen, Jun Ma, Zhaochun Ren:
On the Effectiveness of Unlearning in Session-Based Recommendation. CoRR abs/2312.14447 (2023) - 2022
- [c23]Zhaochun Ren, Zhi Tian, Dongdong Li, Pengjie Ren, Liu Yang, Xin Xin, Huasheng Liang, Maarten de Rijke, Zhumin Chen:
Variational Reasoning about User Preferences for Conversational Recommendation. SIGIR 2022: 165-175 - [c22]Xin Xin, Tiago Pimentel, Alexandros Karatzoglou, Pengjie Ren, Konstantina Christakopoulou, Zhaochun Ren:
Rethinking Reinforcement Learning for Recommendation: A Prompt Perspective. SIGIR 2022: 1347-1357 - [c21]Guojun Yan, Jiahuan Pei, Pengjie Ren, Zhaochun Ren, Xin Xin, Huasheng Liang, Maarten de Rijke, Zhumin Chen:
ReMeDi: Resources for Multi-domain, Multi-service, Medical Dialogues. SIGIR 2022: 3013-3024 - [c20]Xiangyu Zhao, Xin Xin, Weinan Zhang, Li Zhao, Dawei Yin, Grace Hui Yang:
DRL4IR: 3rd Workshop on Deep Reinforcement Learning for Information Retrieval. SIGIR 2022: 3488-3491 - [c19]Dusan Stamenkovic, Alexandros Karatzoglou, Ioannis Arapakis, Xin Xin, Kleomenis Katevas:
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning. WSDM 2022: 957-965 - [c18]Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose:
Supervised Advantage Actor-Critic for Recommender Systems. WSDM 2022: 1186-1196 - [c17]Yu Wang, Xin Xin, Zaiqiao Meng, Joemon M. Jose, Fuli Feng, Xiangnan He:
Learning Robust Recommenders through Cross-Model Agreement. WWW 2022: 2015-2025 - [i15]Jiajia Chen, Xin Xin, Xianfeng Liang, Xiangnan He, Jun Liu:
GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation. CoRR abs/2205.09948 (2022) - [i14]Xin Xin, Tiago Pimentel, Alexandros Karatzoglou, Pengjie Ren, Konstantina Christakopoulou, Zhaochun Ren:
Rethinking Reinforcement Learning for Recommendation: A Prompt Perspective. CoRR abs/2206.07353 (2022) - [i13]Xin Xin, Jiyuan Yang, Hanbing Wang, Jun Ma, Pengjie Ren, Hengliang Luo, Xinlei Shi, Zhumin Chen, Zhaochun Ren:
On the User Behavior Leakage from Recommender System Exposure. CoRR abs/2210.08435 (2022) - [i12]Xiaoyu Zhang, Xin Xin, Dongdong Li, Wenxuan Liu, Pengjie Ren, Zhumin Chen, Jun Ma, Zhaochun Ren:
Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation. CoRR abs/2212.11868 (2022) - 2021
- [b1]Xin Xin:
Deep learning-based implicit feedback recommendation. University of Glasgow, UK, 2021 - [j4]Paula Gómez Duran, Alexandros Karatzoglou, Jordi Vitrià, Xin Xin, Ioannis Arapakis:
Graph Convolutional Embeddings for Recommender Systems. IEEE Access 9: 100173-100184 (2021) - [j3]Bo Chen, Yue Ding, Xin Xin, Yunzhe Li, Yule Wang, Dong Wang:
AIRec: Attentive intersection model for tag-aware recommendation. Neurocomputing 421: 105-114 (2021) - [c16]Yunzhe Li, Yue Ding, Bo Chen, Xin Xin, Yule Wang, Yuxiang Shi, Ruiming Tang, Dong Wang:
Extracting Attentive Social Temporal Excitation for Sequential Recommendation. CIKM 2021: 998-1007 - [c15]Mingyue Cheng, Fajie Yuan, Qi Liu, Xin Xin, Enhong Chen:
Learning Transferable User Representations with Sequential Behaviors via Contrastive Pre-training. ICDM 2021: 51-60 - [c14]Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, Keping Yang:
AutoDebias: Learning to Debias for Recommendation. SIGIR 2021: 21-30 - [c13]Fuli Feng, Weiran Huang, Xiangnan He, Xin Xin, Qifan Wang, Tat-Seng Chua:
Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method. SIGIR 2021: 1208-1218 - [c12]Hao Chen, Xin Xin, Dong Wang, Yue Ding:
Decomposed Collaborative Filtering: Modeling Explicit and Implicit Factors For Recommender Systems. WSDM 2021: 958-966 - [i11]Paula Gómez Duran, Alexandros Karatzoglou, Jordi Vitrià, Xin Xin, Ioannis Arapakis:
Graph Convolutional Embeddings for Recommender Systems. CoRR abs/2103.03587 (2021) - [i10]Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, Keping Yang:
AutoDebias: Learning to Debias for Recommendation. CoRR abs/2105.04170 (2021) - [i9]Yu Wang, Xin Xin, Zaiqiao Meng, Xiangnan He, Joemon M. Jose, Fuli Feng:
Probabilistic and Variational Recommendation Denoising. CoRR abs/2105.09605 (2021) - [i8]Yule Wang, Xin Xin, Yue Ding, Dong Wang:
ICMT: Item Cluster-Wise Multi-Objective Training for Long-Tail Recommendation. CoRR abs/2109.12887 (2021) - [i7]Yunzhe Li, Yue Ding, Bo Chen, Xin Xin, Yule Wang, Yuxiang Shi, Ruiming Tang, Dong Wang:
Extracting Attentive Social Temporal Excitation for Sequential Recommendation. CoRR abs/2109.13539 (2021) - [i6]Dusan Stamenkovic, Alexandros Karatzoglou, Ioannis Arapakis, Xin Xin, Kleomenis Katevas:
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning. CoRR abs/2110.15097 (2021) - [i5]Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose:
Supervised Advantage Actor-Critic for Recommender Systems. CoRR abs/2111.03474 (2021) - 2020
- [c11]Bo Chen, Wei Guo, Ruiming Tang, Xin Xin, Yue Ding, Xiuqiang He, Dong Wang:
TGCN: Tag Graph Convolutional Network for Tag-Aware Recommendation. CIKM 2020: 155-164 - [c10]Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose:
Self-Supervised Reinforcement Learning for Recommender Systems. SIGIR 2020: 931-940 - [i4]Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose:
Graph Highway Networks. CoRR abs/2004.04635 (2020) - [i3]Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose:
Self-Supervised Reinforcement Learning for Recommender Systems. CoRR abs/2006.05779 (2020) - [i2]Fuli Feng, Weiran Huang, Xin Xin, Xiangnan He, Tat-Seng Chua:
Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method. CoRR abs/2010.11797 (2020)
2010 – 2019
- 2019
- [c9]Xin Xin, Bo Chen, Xiangnan He, Dong Wang, Yue Ding, Joemon M. Jose:
CFM: Convolutional Factorization Machines for Context-Aware Recommendation. IJCAI 2019: 3926-3932 - [c8]Bo Chen, Dong Wang, Yue Ding, Xin Xin:
AIRec: Attentive Intersection Model for Tag-Aware Recommendation. ISWC (Satellites) 2019: 17-20 - [c7]Xin Xin, Xiangnan He, Yongfeng Zhang, Yongdong Zhang, Joemon M. Jose:
Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation. SIGIR 2019: 125-134 - [i1]Xin Xin, Xiangnan He, Yongfeng Zhang, Yongdong Zhang, Joemon M. Jose:
Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation. CoRR abs/1904.12796 (2019) - 2018
- [j2]Yue Ding, Dong Wang, Xin Xin, Guoqiang Li, Daniel Sun, Xuezhi Zeng, Rajiv Ranjan:
SCFM: Social and crowdsourcing factorization machines for recommendation. Appl. Soft Comput. 66: 548-556 (2018) - [c6]Xin Xin, Fajie Yuan, Xiangnan He, Joemon M. Jose:
Batch IS NOT Heavy: Learning Word Representations From All Samples. ACL (1) 2018: 1853-1862 - [c5]Fajie Yuan, Xin Xin, Xiangnan He, Guibing Guo, Weinan Zhang, Tat-Seng Chua, Jose M. Joemon:
fBGD: Learning Embeddings From Positive Unlabeled Data with BGD. UAI 2018: 198-207 - 2017
- [j1]Yue Ding, Dong Wang, Guoqiang Li, Daniel Sun, Xin Xin, Shiyou Qian:
Exploiting long-term and short-term preferences and RFID trajectories in shop recommendation. Softw. Pract. Exp. 47(6): 849-865 (2017) - [c4]Litian Yin, Dong Wang, Xin Xin, Yue Ding:
SoGeM: Social Based Generative Model for Top-N Recommendation. ICTAI 2017: 802-806 - [c3]Lini Chen, Xin Xin, Dong Wong, Yue Ding:
HCoM: Item-Based Similarity Model for Heterogeneous Implicit Feedback. MDM 2017: 40-49 - 2016
- [c2]Xin Xin, Dong Wang, Yue Ding, Chen Lini:
FHSM: Factored Hybrid Similarity Methods for Top-N Recommender Systems. APWeb (2) 2016: 98-110 - 2015
- [c1]Yue Ding, Dong Wang, Xin Xin:
Novel Approaches for Shop Recommendation in Large Shopping Mall Scenario: From Matrix Factorization to Tensor Decomposition. KSEM 2015: 471-482
Coauthor Index
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