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Recommendation systems have witnessed significant advancements and have been widely used over the past decades.
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Language models are unsupervised multitask learners
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Content-based group recommender systems: A general taxonomy and further improvements
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Multitask prompted training enables zero-shot task generalization
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Challenges and research opportunities in ecommerce search and recommendations. In ACM Sigir Forum , Vol. 54. ACM New York, NY, USA, 1–23
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MMGCN: Multi-modal graph convolution network for personalized recommendation of micro-video. In Proceedings of the 27th ACM international conference on multimedia . 1437–1445
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NPA: neural news recommendation with personalized attention. In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining . 2576–2584
Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang, and Xing Xie. 2019 · 2019
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XLNet: Generalized Autoregressive Pretraining for Language Understanding
Z. Yang, Z. Dai, Y. Yang, J. Carbonell, R. Salakhutdinov, and Q. V. Le. 2019 · 2019
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Privacy-aware smart city: A case study in collaborative filtering recommender systems
Feng Zhang, Victor E Lee, Ruoming Jin, Saurabh Garg, Kim-Kwang Raymond Choo, Michele Maasberg, Lijun Dong, and Chi Cheng. 2019a · 2019
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DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation
Y. Zhang, S. Sun, M. Galley, Y. C. Chen, C. Brockett, X. Gao, J. Gao, J. Liu, and B. Dolan. 2019b · 2019
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Recommending what video to watch next: a multitask ranking system. In Proceedings of the 13th ACM Conference on Recommender Systems . 43–51
Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, and Ed Chi. 2019 · 2019
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A systematic study on the recommender systems in the E-commerce
Pegah Malekpour Alamdari, Nima Jafari Navimipour, Mehdi Hosseinzadeh, Ali Asghar Safaei, and Aso Darwesh. 2020 · 2020
Cited alongside, same era.
Language Models as Recommender Systems: Evaluations and Limitations. In I (Still) Can’t Believe It’s Not Better! NeurIPS 2021 Workshop
Yuhui Zhang, HAO DING, Zeren Shui, Yifei Ma, James Zou, Anoop Deoras, and Hao Wang. 2021 · 2021
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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 · 2022
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Recommendation as language processing (rlp): A unified pretrain, personalized prompt & predict paradigm (p5). In Proceedings of the 16th ACM Conference on Recommender Systems . 299–315
Shijie Geng, Shuchang Liu, Zuohui Fu, Yingqiang Ge, and Yongfeng Zhang. 2022 · 2022
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An ecommerce recommendation algorithm based on link prediction
Guoguang Liu. 2022 · 2022
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“It is just a flu”: Assessing the Effect of Watch History on YouTube’s Pseudoscientific Video Recommendations. In Proceedings of the international AAAI conference on web and social media , Vol. 16. 723–734
Kostantinos Papadamou, Savvas Zannettou, Jeremy Blackburn, Emiliano De Cristofaro, Gianluca Stringhini, and Michael Sirivianos. 2022 · 2022
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A Novel Deep Neural-based Music Recommendation Method considering User and Song Data. In 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) . IEEE, 1–7
Jagendra Singh, Mohammad Sajid, Chandra Shekhar Yadav, Shashank Sheshar Singh, and Manthan Saini. 2022 · 2022
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Revisiting Bundle Recommendation: Datasets, Tasks, Challenges and Opportunities for Intent-aware Product Bundling. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval . 2900–2911
Zhu Sun, Jie Yang, Kaidong Feng, Hui Fang, Xinghua Qu, and Yew Soon Ong. 2022 · 2022
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Decoupled side information fusion for sequential recommendation. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval . 1611–1621
Yueqi Xie, Peilin Zhou, and Sunghun Kim. 2022 · 2022
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GreenPLM: Cross-lingual pre-trained language models conversion with (almost) no cost
Qingcheng Zeng, Lucas Garay, Peilin Zhou, Dading Chong, Yining Hua, Jiageng Wu, Yikang Pan, Han Zhou, and Jie Yang. 2022 · 2022
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Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, et al · 2023
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Chataug: Leveraging chatgpt for text data augmentation
Haixing Dai, Zhengliang Liu, Wenxiong Liao, Xiaoke Huang, Zihao Wu, Lin Zhao, Wei Liu, Ninghao Liu, Sheng Li, Dajiang Zhu, et al · 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 · 2023
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Is ChatGPT a good translator? A preliminary study
Wenxiang Jiao, Wenxuan Wang, Jen-tse Huang, Xing Wang, and Zhaopeng Tu. 2023 · 2023
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Benchmarking Large Language Models on CMExam–A Comprehensive Chinese Medical Exam Dataset
Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, et al · 2023
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OpenAI. 2023 · 2023
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Rethinking multi-interest learning for candidate matching in recommender systems. In Proceedings of the 17th ACM Conference on Recommender Systems . 283–293
Yueqi Xie, Jingqi Gao, Peilin Zhou, Qichen Ye, Yining Hua, Jae Boum Kim, Fangzhao Wu, and Sunghun Kim. 2023 · 2023
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A survey of attack detection approaches in collaborative filtering recommender systems
Fatemeh Rezaimehr and Chitra Dadkhah. 2021 · 2066
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Feedrec: News feed recommendation with various user feedbacks. In Proceedings of the ACM Web Conference 2022 . 2088–2097
Chuhan Wu, Fangzhao Wu, Tao Qi, Qi Liu, Xuan Tian, Jie Li, Wei He, Yongfeng Huang, and Xing Xie. 2022 · 2097
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