OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)
Shijie Geng, Shuchang Liu, Zuohui Fu, et al.
(2022), pp. 299-315
Closed Access | Times Cited: 180
Shijie Geng, Shuchang Liu, Zuohui Fu, et al.
(2022), pp. 299-315
Closed Access | Times Cited: 180
Showing 1-25 of 180 citing articles:
Self-Supervised Learning for Recommender Systems: A Survey
Junliang Yu, Hongzhi Yin, Xin Xia, et al.
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 36, Iss. 1, pp. 335-355
Open Access | Times Cited: 154
Junliang Yu, Hongzhi Yin, Xin Xia, et al.
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 36, Iss. 1, pp. 335-355
Open Access | Times Cited: 154
TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation
Keqin Bao, Jizhi Zhang, Yang Zhang, et al.
(2023), pp. 1007-1014
Open Access | Times Cited: 95
Keqin Bao, Jizhi Zhang, Yang Zhang, et al.
(2023), pp. 1007-1014
Open Access | Times Cited: 95
Large Language Models are Zero-Shot Rankers for Recommender Systems
Yupeng Hou, Junjie Zhang, Zihan Lin, et al.
Lecture notes in computer science (2024), pp. 364-381
Closed Access | Times Cited: 71
Yupeng Hou, Junjie Zhang, Zihan Lin, et al.
Lecture notes in computer science (2024), pp. 364-381
Closed Access | Times Cited: 71
Recommender Systems in the Era of Large Language Models (LLMs)
Zihuai Zhao, Wenqi Fan, Jiatong Li, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 11, pp. 6889-6907
Open Access | Times Cited: 61
Zihuai Zhao, Wenqi Fan, Jiatong Li, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 11, pp. 6889-6907
Open Access | Times Cited: 61
Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders
Yupeng Hou, Zhankui He, Julian McAuley, et al.
Proceedings of the ACM Web Conference 2022 (2023), pp. 1162-1171
Open Access | Times Cited: 60
Yupeng Hou, Zhankui He, Julian McAuley, et al.
Proceedings of the ACM Web Conference 2022 (2023), pp. 1162-1171
Open Access | Times Cited: 60
Prompt Distillation for Efficient LLM-based Recommendation
Lei Li, Yongfeng Zhang, Li Chen
(2023), pp. 1348-1357
Closed Access | Times Cited: 44
Lei Li, Yongfeng Zhang, Li Chen
(2023), pp. 1348-1357
Closed Access | Times Cited: 44
A survey on large language models for recommendation
Likang Wu, Zhi Zheng, Zhaopeng Qiu, et al.
World Wide Web (2024) Vol. 27, Iss. 5
Closed Access | Times Cited: 41
Likang Wu, Zhi Zheng, Zhaopeng Qiu, et al.
World Wide Web (2024) Vol. 27, Iss. 5
Closed Access | Times Cited: 41
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences
Scott Sanner, Krisztian Balog, Filip Radlinski, et al.
(2023), pp. 890-896
Open Access | Times Cited: 39
Scott Sanner, Krisztian Balog, Filip Radlinski, et al.
(2023), pp. 890-896
Open Access | Times Cited: 39
When large language models meet personalization: perspectives of challenges and opportunities
Jing Chen, Zheng Liu, Xu Huang, et al.
World Wide Web (2024) Vol. 27, Iss. 4
Open Access | Times Cited: 39
Jing Chen, Zheng Liu, Xu Huang, et al.
World Wide Web (2024) Vol. 27, Iss. 4
Open Access | Times Cited: 39
Representation Learning with Large Language Models for Recommendation
Xubin Ren, Wei Wei, Lianghao Xia, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3464-3475
Open Access | Times Cited: 29
Xubin Ren, Wei Wei, Lianghao Xia, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3464-3475
Open Access | Times Cited: 29
How Can Recommender Systems Benefit from Large Language Models: A Survey
Jianghao Lin, Xinyi Dai, Yunjia Xi, et al.
ACM transactions on office information systems (2024)
Open Access | Times Cited: 26
Jianghao Lin, Xinyi Dai, Yunjia Xi, et al.
ACM transactions on office information systems (2024)
Open Access | Times Cited: 26
Personalized Prompt for Sequential Recommendation
Yiqing Wu, Ruobing Xie, Yongchun Zhu, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 7, pp. 3376-3389
Open Access | Times Cited: 15
Yiqing Wu, Ruobing Xie, Yongchun Zhu, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 7, pp. 3376-3389
Open Access | Times Cited: 15
Artificial intelligence foundation and pre-trained models: Fundamentals, applications, opportunities, and social impacts
Adam Kolides, Alyna Nawaz, Anshu Rathor, et al.
Simulation Modelling Practice and Theory (2023) Vol. 126, pp. 102754-102754
Closed Access | Times Cited: 37
Adam Kolides, Alyna Nawaz, Anshu Rathor, et al.
Simulation Modelling Practice and Theory (2023) Vol. 126, pp. 102754-102754
Closed Access | Times Cited: 37
Prompt Learning for News Recommendation
Zizhuo Zhang, Bang Wang
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2023), pp. 227-237
Open Access | Times Cited: 35
Zizhuo Zhang, Bang Wang
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2023), pp. 227-237
Open Access | Times Cited: 35
Leveraging Large Language Models for Sequential Recommendation
Jesse Harte, Wouter Zorgdrager, Πάνος Λουρίδας, et al.
(2023), pp. 1096-1102
Open Access | Times Cited: 32
Jesse Harte, Wouter Zorgdrager, Πάνος Λουρίδας, et al.
(2023), pp. 1096-1102
Open Access | Times Cited: 32
Denoising and Prompt-Tuning for Multi-Behavior Recommendation
Chi Zhang, Rui Chen, Xiangyu Zhao, et al.
Proceedings of the ACM Web Conference 2022 (2023), pp. 1355-1363
Open Access | Times Cited: 29
Chi Zhang, Rui Chen, Xiangyu Zhao, et al.
Proceedings of the ACM Web Conference 2022 (2023), pp. 1355-1363
Open Access | Times Cited: 29
ChatDiet: Empowering personalized nutrition-oriented food recommender chatbots through an LLM-augmented framework
Zhongqi Yang, Elahe Khatibi, Nitish Nagesh, et al.
Smart Health (2024) Vol. 32, pp. 100465-100465
Open Access | Times Cited: 14
Zhongqi Yang, Elahe Khatibi, Nitish Nagesh, et al.
Smart Health (2024) Vol. 32, pp. 100465-100465
Open Access | Times Cited: 14
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
Jianghao Lin, Rong Shan, Chenxu Zhu, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3497-3508
Open Access | Times Cited: 13
Jianghao Lin, Rong Shan, Chenxu Zhu, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3497-3508
Open Access | Times Cited: 13
GenRec: Large Language Model for Generative Recommendation
Jianchao Ji, Zelong Li, Shuyuan Xu, et al.
Lecture notes in computer science (2024), pp. 494-502
Closed Access | Times Cited: 12
Jianchao Ji, Zelong Li, Shuyuan Xu, et al.
Lecture notes in computer science (2024), pp. 494-502
Closed Access | Times Cited: 12
Collaborative Large Language Model for Recommender Systems
Yaochen Zhu, Liang Wu, Qi Guo, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3162-3172
Open Access | Times Cited: 12
Yaochen Zhu, Liang Wu, Qi Guo, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3162-3172
Open Access | Times Cited: 12
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)
Yashar Deldjoo, Zhankui He, Julian McAuley, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 6448-6458
Open Access | Times Cited: 11
Yashar Deldjoo, Zhankui He, Julian McAuley, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 6448-6458
Open Access | Times Cited: 11
Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach
Junjie Zhang, Ruobing Xie, Yupeng Hou, et al.
ACM transactions on office information systems (2024)
Open Access | Times Cited: 11
Junjie Zhang, Ruobing Xie, Yupeng Hou, et al.
ACM transactions on office information systems (2024)
Open Access | Times Cited: 11
From Traditional Recommender Systems to GPT-Based Chatbots: A Survey of Recent Developments and Future Directions
Tamim M. Al-Hasan, Aya Nabil Sayed, Fayçal Bensaali, et al.
Big Data and Cognitive Computing (2024) Vol. 8, Iss. 4, pp. 36-36
Open Access | Times Cited: 10
Tamim M. Al-Hasan, Aya Nabil Sayed, Fayçal Bensaali, et al.
Big Data and Cognitive Computing (2024) Vol. 8, Iss. 4, pp. 36-36
Open Access | Times Cited: 10
AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems
Junjie Zhang, Yupeng Hou, Ruobing Xie, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3679-3689
Open Access | Times Cited: 10
Junjie Zhang, Yupeng Hou, Ruobing Xie, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3679-3689
Open Access | Times Cited: 10
ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction
Jianghao Lin, Bo Chen, Hangyu Wang, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3319-3330
Open Access | Times Cited: 9
Jianghao Lin, Bo Chen, Hangyu Wang, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3319-3330
Open Access | Times Cited: 9
