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Recommender systems help users navigate information overload by providing personalized recommendations aligned with their preferences.
Attentive collaborative filtering: Multimedia recommendation with item-and component-level attention
Jingyuan Chen, Hanwang Zhang, Xiangnan He, Liqiang Nie, Wei Liu, and Tat-Seng Chua. 2017 · 2017
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Learning to generate product reviews from attributes
Li Dong, Shaohan Huang, Furu Wei, Mirella Lapata, Ming Zhou, and Ke Xu. 2017 · 2017
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Neural rating regression with abstractive tips generation for recommendation
Piji Li, Zihao Wang, Zhaochun Ren, Lidong Bing, and Wai Lam. 2017 · 2017
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Graph convolutional neural networks for web-scale recommender systems
Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L Hamilton, and Jure Leskovec. 2018 · 2018
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Justifying recommendations using distantly-labeled reviews and fine-grained aspects
Jianmo Ni, Jiacheng Li, and Julian McAuley. 2019 · 2019
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Neural graph collaborative filtering
Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, and Tat-Seng Chua. 2019 · 2019
Earlier work this paper cites.
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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Bleurt: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur P Parikh. 2020 · 2020
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2020 · 2020
Cited alongside, same era.
Neural collaborative reasoning
Hanxiong Chen, Shaoyun Shi, Yunqi Li, and Yongfeng Zhang. 2021 · 2021
Cited alongside, same era.
Personalized transformer for explainable recommendation
Lei Li, Yongfeng Zhang, and Li Chen. 2021 · 2021
Cited alongside, same era.
Self-supervised learning for large-scale item recommendations
Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix Yu, Ting Chen, Aditya Menon, Lichan Hong, Ed H Chi, Steve Tjoa, Jieqi Kang, et al. 2021 · 2021
Cited alongside, same era.
Bartscore: Evaluating generated text as text generation
Weizhe Yuan, Graham Neubig, and Pengfei Liu. 2021 · 2021
Cited alongside, same era.
Towards universal sequence representation learning for recommender systems
Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, and Ji-Rong Wen. 2022 · 2022
Disentangled representation learning with large language models for text-attributed graphs
Yijian Qin, Xin Wang, Ziwei Zhang, and Wenwu Zhu. 2023 · 2023
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Disentangled contrastive collaborative filtering
Xubin Ren, Lianghao Xia, Jiashu Zhao, Dawei Yin, and Chao Huang. 2023 · 2023
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Is chatgpt a good nlg evaluator? a preliminary study
Jiaan Wang, Yunlong Liang, Fandong Meng, Zengkui Sun, Haoxiang Shi, Zhixu Li, Jinan Xu, Jianfeng Qu, and Jie Zhou. 2023 · 2023
Later among the works it cites.
Towards open-world recommendation with knowledge augmentation from large language models
Yunjia Xi, Weiwen Liu, Jianghao Lin, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Rui Zhang, and Yong Yu. 2023 · 2023
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Automated self-supervised learning for recommendation
Lianghao Xia, Chao Huang, Chunzhen Huang, Kangyi Lin, Tao Yu, and Ben Kao. 2023 · 2023
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Cited alongside, same era.
Uctopic: Unsupervised contrastive learning for phrase representations and topic mining
Jiacheng Li, Jingbo Shang, and Julian McAuley. 2022 · 2022
Cited alongside, same era.
Personalized prompt learning for explainable recommendation
Lei Li, Yongfeng Zhang, and Li Chen. 2023 · 2023
Cited alongside, same era.
Generative-contrastive graph learning for recommendation
Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, and Meng Wang. 2023a
Cited in the paper.
Knowledge graph self-supervised rationalization for recommendation
Yuhao Yang, Chao Huang, Lianghao Xia, and Chunzhen Huang. 2023b
Cited in the paper.
Star-gcn: Stacked and reconstructed graph convolutional networks for recommender systems
Jiani Zhang, Xingjian Shi, Shenglin Zhao, and Irwin King. 2019a
Cited in the paper.
Deep learning based recommender system: A survey and new perspectives
Shuai Zhang, Lina Yao, Aixin Sun, and Yi Tay. 2019b
Cited in the paper.
Personalized showcases: Generating multi-modal explanations for recommendations
An Yan, Zhankui He, Jiacheng Li, Tianyang Zhang, and Julian McAuley. 2023 · 2023
Later among the works it cites.
Representation learning with large language models for recommendation
Xubin Ren, Wei Wei, Lianghao Xia, Lixin Su, Suqi Cheng, Junfeng Wang, Dawei Yin, and Chao Huang. 2024 · 2024
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