| Reference: | [1] Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, et al., Language Models are Few-Shot Learners, Advances in Neural Information Processing Systems, 2020
[2] Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, et al., A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys), In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
[3] Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, et al., Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation, In Proceedings of the 37th International Conference on Neural Information Processing Systems, 2023
[4] Jinhyuk Lee, Feiyang Chen, Sahil Dua, Daniel Cer, Madhuri Shanbhogue, et al., Gemini Embedding: Generalizable Embeddings from Gemini, CoRR, 2025
[5] Jianghao Lin, Xinyi Dai, Yunjia Xi, Weiwen Liu, Bo Chen, et al., How Can Recommender Systems Benefit from Large Language Models: A Survey, ACM Transactions on Information Systems, Vol. 43, No. 2, 2025
[6] Dong-Ho Lee, Adam Kraft, Long Jin, Nikhil Mehta, Taibai Xu, et al., STAR: A Simple Training-free Approach for Recommendations using Large Language Models, CoRR, 2024
[7] Junling Liu, Chao Liu, Peilin Zhou, Qichen Ye, Dading Chong, et al., LLMRec: Benchmarking Large Language Models on Recommendation Task, CoRR, 2023
[8] Junling Liu, Chao Liu, Peilin Zhou, Renjie Lv, Kang Zhou, et al., Is ChatGPT a Good Recommender? A Preliminary Study, In Proceedings of the 1st Workshop on Recommendation with Generative Models, co-located with the 32nd ACM International Conference on Information and Knowledge Management, 2023
[9] Michael Xieyang Liu, Frederick Liu, Alexander J. Fiannaca, Terry Koo, Lucas Dixon, et al., We Need Structured Output: Towards User-centered Constraints on Large Language Model Output, Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2024
[10] Sebastian Lubos, Thi Ngoc Trang Tran, Alexander Felfernig, Seda Polat Erdeniz, and Viet-Man Le, LLM-generated Explanations for Recommender Systems, Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization, 2024
[11] Yueqing Liang, Liangwei Yang, Chen Wang, Xiongxiao Xu, Philip S. Yu, et al., Taxonomy-Guided Zero-Shot Recommendations with LLMs, In Proceedings of the 31st International Conference on Computational Linguistics, 2025
[12] Humza Naveed, Asad Ullah Khan, Shi Qiu, Muhammad Saqib, Saeed Anwar, et al., A Comprehensive Overview of Large Language Models, ACM Transactions on Intelligent Systems and Technology, 2025
[13] Wenqi Sun, Ruobing Xie, Junjie Zhang, Wayne Xin Zhao, Leyu Lin, et al., Generative Next-Basket Recommendation, In Proceedings of the 17th ACM Conference on Recommender Systems, 2023
[14] Lei Li, Yongfeng Zhang, Dugang Liu, and Li Chen, Large Language Models for Generative Recommendation: A Survey and Visionary Discussions, Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, 2024
[15] Joni Salminen, Chang Liu, Wenjing Pian, Jianxing Chi, Essi Häyhänen, et al., Deus Ex Machina and Personas from Large Language Models: Investigating the Composition of AI-Generated Persona Descriptions, In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems, 2024
[16] Zhufeng Shao, Shoujin Wang, Qian Zhang, Wenpeng Lu, Zhao Li, An Empirical Study of Next-basket Recommendations, CoRR, 2023
[17] Hanbing Wang, Xiaorui Liu, Wenqi Fan, Xiangyu Zhao, Venkataramana Kini, et al., Rethinking Large Language Model Architectures for Sequential Recommendations, CoRR, 2024
[18] Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, et al., A Survey on Large Language Models for Recommendation, World Wide Web, Vol. 27, No. 5, 2024
[19] Shuyuan Xu, Wenyue Hua, and Yongfeng Zhang, OpenP5: An Open-Source Platform for Developing, Training, and Evaluating LLM-based Recommender Systems, In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024
[20] Fan Yang, Zheng Chen, Ziyan Jiang, Eunah Cho, Xiaojiang Huang, et al., PALR: Personalization Aware LLMs for Recommendation, arXiv:2305.07622, 2023
[21] Joyce Zhou, Yijia Dai, and Thorsten Joachims, Language-Based User Profiles for Recommendation, CoRR, 2024 |
