Large Language Models for Recommendation: Past, Present, and Future
Author:
Affiliation:
1. University of Science and Technology in China, Hefei, China
2. National University of Singapore, Singapore, Singapore
3. University of Science and Technology in China, Hefei, Anhui, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3626772.3661383
Reference59 articles.
1. Information Retrieval meets Large Language Models: A strategic report from Chinese IR community
2. Keqin Bao et al. 2023. A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems. CoRR abs/2308.08434 (2023). arXiv:2308.08434
3. Keqin Bao et al. 2023. Large Language Models for Recommendation: Progresses and Future Directions. SIGIR-AP (2023).
4. Keqin Bao et al. 2023. TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. In RecSys. ACM 1007--1014.
5. Lukas Berglund et al. 2023. The Reversal Curse: LLMs trained on - is Bfail to learn B is Ä. arXiv preprint arXiv:2309.12288 (2023).
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