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Recently, there has been growing interest in developing the next-generation recommender systems (RSs) based on pretrained large language models (LLMs).
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Jacob Devlin Ming-Wei Chang Kenton and Lee Kristina Toutanova · 2019
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BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer
Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou, and Peng Jiang · 2019
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Embarrassingly shallow autoencoders for sparse data
Harald Steck · 2019
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Exploring the limits of transfer learning with a unified text-to-text transformer
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S3-Rec: Self-supervised learning for sequential recommendation with mutual information maximization
Kun Zhou, Hui Wang, Wayne Xin Zhao, Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, and Ji-Rong Wen · 2020
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Advances in collaborative filtering
Yehuda Koren, Steffen Rendle, and Robert Bell · 2021
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant · 2021
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Emergent abilities of large language models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al · 2022
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Variational bandwidth auto-encoder for hybrid recommender systems
Yaochen Zhu and Zhenzhong Chen · 2022
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A language-based recommendation system for material discovery
Jiaxing Qu, Yuxuan Richard Xie, and Elif Ertekin · 2023
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Personalized prompt learning for explainable recommendation
Lei Li, Yongfeng Zhang, and Li Chen · 2023
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Chat-Rec: Towards interactive and explainable llms-augmented recommender system
Yunfan Gao, Tao Sheng, Youlin Xiang, Yun Xiong, Haofen Wang, and Jiawei Zhang · 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 · 2023
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Recommendation as instruction following: A large language model empowered recommendation approach
Junjie Zhang, Ruobing Xie, Yupeng Hou, Wayne Xin Zhao, Leyu Lin, and Ji-Rong Wen · 2023
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M6-rec: Generative pretrained language models are open-ended recommender systems
Zeyu Cui, Jianxin Ma, Chang Zhou, Jingren Zhou, and Hongxia Yang · 2022
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Recommendation as language processing (RLP): A unified pretrain, personalized prompt & predict paradigm (P5)
Shijie Geng, Shuchang Liu, Zuohui Fu, Yingqiang Ge, and Yongfeng Zhang · 2022
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Mutually-regularized dual collaborative variational auto-encoder for recommendation systems
Yaochen Zhu and Zhenzhong Chen · 2022
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Where to go next for recommender systems? ID vs. modality-based recommender models revisited
Zheng Yuan, Fajie Yuan, Yu Song, Youhua Li, Junchen Fu, Fei Yang, Yunzhu Pan, and Yongxin Ni · 2023
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Path-specific counterfactual fairness for recommender systems
Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, and Jundong Li · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al · 2023
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LlaMA: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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Large language models as zero-shot conversational recommenders
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Palr: Personalization aware llms for recommendation
Fan Yang, Zheng Chen, Ziyan Jiang, Eunah Cho, Xiaojiang Huang, and Yanbin Lu · 2023
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GenRec: Large language model for generative recommendation
Jianchao Ji, Zelong Li, Shuyuan Xu, Wenyue Hua, Yingqiang Ge, Juntao Tan, and Yongfeng Zhang · 2023
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Leveraging large language models for pre-trained recommender systems
Zhixuan Chu, Hongyan Hao, Xin Ouyang, Simeng Wang, Yan Wang, Yue Shen, Jinjie Gu, Qing Cui, Longfei Li, Siqiao Xue, et al · 2023
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How to index item ids for recommendation foundation models
Wenyue Hua, Shuyuan Xu, Yingqiang Ge, and Yongfeng Zhang · 2023
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Recent advances in natural language processing via large pre-trained language models: A survey
Bonan Min, Hayley Ross, Elior Sulem, Amir Pouran Ben Veyseh, Thien Huu Nguyen, Oscar Sainz, Eneko Agirre, Ilana Heintz, and Dan Roth · 2023
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Peng Liu, Lemei Zhang, and Jon Atle Gulla · 2023
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How can recommender systems benefit from large language models: A survey
Jianghao Lin, Xinyi Dai, Yunjia Xi, Weiwen Liu, Bo Chen, Xiangyang Li, Chenxu Zhu, Huifeng Guo, Yong Yu, Ruiming Tang, et al · 2023
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