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Recommender systems play a central role in numerous real-life applications, yet evaluating their performance remains a significant challenge due to the gap between offline metrics and online behaviors.
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Matrix factorization techniques for recommender systems
Yehuda Koren, Robert Bell, and Chris Volinsky. 2009 · 2009
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Learning word vectors for sentiment analysis
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Pathsim: Meta path-based top-k similarity search in heterogeneous information networks
Yizhou Sun, Jiawei Han, Xifeng Yan, Philip S Yu, and Tianyi Wu. 2011 · 2011
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Leveraging social connections to improve personalized ranking for collaborative filtering
Tong Zhao, Julian McAuley, and Irwin King. 2014 · 2014
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Towards conversational recommender systems
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Jun Xiao, Hao Ye, Xiangnan He, Hanwang Zhang, Fei Wu, and Tat-Seng Chua. 2017 · 2017
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Variational autoencoders for collaborative filtering
Dawen Liang, Rahul G Krishnan, Matthew D Hoffman, and Tony Jebara. 2018 · 2018
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User personality and user satisfaction with recommender systems
Tien T Nguyen, F Maxwell Harper, Loren Terveen, and Joseph A Konstan. 2018 · 2018
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Measuring the business value of recommender systems
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Deep learning based recommender system: A survey and new perspectives
Shuai Zhang, Lina Yao, Aixin Sun, and Yi Tay. 2019 · 2019
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Lightgcn: Simplifying and powering graph convolution network for recommendation
Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang, and Meng Wang. 2020 · 2020
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Estimation-action-reflection: Towards deep interaction between conversational and recommender systems
Wenqiang Lei, Xiangnan He, Yisong Miao, Qingyun Wu, Richang Hong, Min-Yen Kan, and Tat-Seng Chua. 2020 · 2020
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An exploration of the relation between the visual attributes of thumbnails and the view-through of videos: The case of branded video content
Byungwan Koh and Fuquan Cui. 2022 · 2022
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Tenrec: A large-scale multipurpose benchmark dataset for recommender systems
Guanghu Yuan, Fajie Yuan, Yudong Li, Beibei Kong, Shujie Li, Lei Chen, Min Yang, Chenyun Yu, Bo Hu, Zang Li, Yu Xu, and Xiaohu Qie. 2022 · 2022
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Can large language models be an alternative to human evaluations?
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Pyabsa: A modularized framework for reproducible aspect-based sentiment analysis
Heng Yang, Chen Zhang, and Ke Li. 2023 · 2023
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On generative agents in recommendation
An Zhang, Leheng Sheng, Yuxin Chen, Hao Li, Yang Deng, Xiang Wang, and Tat-Seng Chua. 2023 · 2023
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Kuaisim: A comprehensive simulator for recommender systems
Kesen Zhao, Shuchang Liu, Qingpeng Cai, Xiangyu Zhao, Ziru Liu, Dong Zheng, Peng Jiang, and Kun Gai. 2023 · 2023
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Large language models are zero-shot rankers for recommender systems
Yupeng Hou, Junjie Zhang, Zihan Lin, Hongyu Lu, Ruobing Xie, Julian McAuley, and Wayne Xin Zhao. 2024 · 2024
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Recent developments in recommender systems: A survey
Yang Li, Kangbo Liu, Ranjan Satapathy, Suhang Wang, and Erik Cambria. 2024 · 2024
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Biases in scholarly recommender systems: impact, prevalence, and mitigation
Michael Färber, Melissa Coutinho, and Shuzhou Yuan. 2023 · 2023
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Large language models as zero-shot conversational recommenders
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Recommender ai agent: Integrating large language models for interactive recommendations
Xu Huang, Jianxun Lian, Yuxuan Lei, Jing Yao, Defu Lian, and Xing Xie. 2023 · 2023
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Do llms understand user preferences? evaluating llms on user rating prediction
Wang-Cheng Kang, Jianmo Ni, Nikhil Mehta, Maheswaran Sathiamoorthy, Lichan Hong, Ed Chi, and Derek Zhiyuan Cheng. 2023 · 2023
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Gpt4rec: A generative framework for personalized recommendation and user interests interpretation
Jinming Li, Wentao Zhang, Tian Wang, Guanglei Xiong, Alan Lu, and Gerard Medioni. 2023 · 2023
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User behavior simulation with large language model based agents
Lei Wang, Jingsen Zhang, Hao Yang, Zhiyuan Chen, Jiakai Tang, Zeyu Zhang, Xu Chen, Yankai Lin, Ruihua Song, Wayne Xin Zhao, and 1 others. 2023a
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Recmind: Large language model powered agent for recommendation
Yancheng Wang, Ziyan Jiang, Zheng Chen, Fan Yang, Yingxue Zhou, Eunah Cho, Xing Fan, Xiaojiang Huang, Yanbin Lu, and Yingzhen Yang. 2023b
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Yuqing Liu, Yu Wang, Lichao Sun, and Philip S Yu. 2024 · 2024
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Llm-enhanced user-item interactions: Leveraging edge information for optimized recommendations
Xinyuan Wang, Liang Wu, Liangjie Hong, Hao Liu, and Yanjie Fu. 2024 · 2024
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Minicpm-v: A gpt-4v level mllm on your phone
Yuan Yao, Tianyu Yu, Ao Zhang, Chongyi Wang, Junbo Cui, Hongji Zhu, Tianchi Cai, Haoyu Li, Weilin Zhao, Zhihui He, Qianyu Chen, Huarong Zhou, Zhensheng Zou, Haoye Zhang, Shengding Hu, Zhi Zheng, Jie Zhou, Jie Cai, Xu Han, and 4 others. 2024 · 2024
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Evaluating large language models as generative user simulators for conversational recommendation
Se-eun Yoon, Zhankui He, Jessica Maria Echterhoff, and Julian McAuley. 2024 · 2024
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Agentcf: Collaborative learning with autonomous language agents for recommender systems
Junjie Zhang, Yupeng Hou, Ruobing Xie, Wenqi Sun, Julian McAuley, Wayne Xin Zhao, Leyu Lin, and Ji-Rong Wen. 2024b · 2024
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