Large Language Models for Next Point-of-Interest Recommendation-Reference-Cited by-同舟云学术

Large Language Models for Next Point-of-Interest Recommendation

Published:2024-07-10 Issue: Volume:35 Page:1463-1472
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Container-title:Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Li Peibo¹^ORCID,de Rijke Maarten²^ORCID,Xue Hao¹^ORCID,Ao Shuang¹^ORCID,Song Yang¹^ORCID,Salim Flora D.¹^ORCID

Affiliation:

1. University of New South Wales, Sydney, NSW, Australia

2. University of Amsterdam, Amsterdam, Netherlands

Funder

Australian Research Council Centre of Excellence for Automated Decision-Making and Society

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626772.3657840

Reference37 articles.

1. Tom Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared D Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell et al. 2020. Language Models are Few-shot Learners. In Advances in neural information processing systems Vol. 33. 1877--1901.

2. Ching Chang Wen-Chih Peng and Tien-Fu Chen. 2023. LLM4TS: Two-Stage Fine-Tuning for Time-Series Forecasting with Pre-Trained LLMs. arXiv preprint arXiv:2308.08469.

3. Yukang Chen Shengju Qian Haotian Tang Xin Lai Zhijian Liu Song Han and Jiaya Jia. 2023. LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models. arXiv:2309.12307.

4. Chen Cheng, Haiqin Yang, Michael R. Lyu, and Irwin King. 2013. Where You Like to Go Next: Successive Point-of-Interest Recommendation. In IJCAI 2013, Proceedings of the 23rd International Joint Conference on Artificial Intelligence, Beijing, China, August 3--9, 2013, Francesca Rossi (Ed.). IJCAI/AAAI, 2605--2611.

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