Where to Move Next: Zero-shot Generalization of LLMs for Next POI Recommendation

D. Yang, D. Zhang, V. W. Zheng, and Z. Yu, “Modeling user activity preference by leveraging user spatial temporal characteristics in lbsns,” IEEE Transactions on Systems, Man, and Cybernetics: Systems , vol. 45, no. 1, pp. 129–142, 2014

2014

Earlier work this paper cites.

S. Feng, G. Cong, B. An, and Y. M. Chee, “Poi2vec: Geographical latent representation for predicting future visitors,” in Proceedings of the AAAI Conference on Artificial Intelligence , vol. 31, no. 1, 2017

2017

Earlier work this paper cites.

X. He, L. Liao, H. Zhang, L. Nie, X. Hu, and T.-S. Chua, “Neural collaborative filtering,” in WWW , 2017, pp. 173–182

2017

Earlier work this paper cites.

S. Feng, L. V. Tran, G. Cong, L. Chen, J. Li, and F. Li, “Hme: A hyperbolic metric embedding approach for next-poi recommendation,” in SIGIR , 2020, pp. 1429–1438

2020

Earlier work this paper cites.

P. Sánchez and A. Bellogín, “Point-of-interest recommender systems based on location-based social networks: a survey from an experimental perspective,” ACM Computing Surveys (CSUR) , vol. 54, no. 11s, pp. 1–37, 2022

2022

Earlier work this paper cites.

S. Yang, J. Liu, and K. Zhao, “Getnext: trajectory flow map enhanced transformer for next poi recommendation,” in SIGIR , 2022

2022

Earlier work this paper cites.

L. Zhang, Z. Sun, Z. Wu, J. Zhang, Y. S. Ong, and X. Qu, “Next point-of-interest recommendation with inferring multi-step future preferences,” in IJCAI , 2022, pp. 3751–3757

2022

Earlier work this paper cites.

F. Yin, Y. Liu, Z. Shen, L. Chen, S. Shang, and P. Han, “Next poi recommendation with dynamic graph and explicit dependency,” in AAAI , vol. 37, no. 4, 2023, pp. 4827–4834

2023

Earlier work this paper cites.

C. Duan, W. Fan, W. Zhou, H. Liu, and J. Wen, “Clsprec: Contrastive learning of long and short-term preferences for next poi recommendation,” in CIKM , 2023, pp. 473–482

2023

Earlier work this paper cites.

X. Yan, T. Song, Y. Jiao, J. He, J. Wang, R. Li, and W. Chu, “Spatio-temporal hypergraph learning for next poi recommendation,” in SIGIR , 2023, pp. 403–412

2023

Earlier work this paper cites.

R. Manvi, S. Khanna, G. Mai, M. Burke, D. Lobell, and S. Ermon, “Geollm: Extracting geospatial knowledge from large language models,” arXiv preprint arXiv:2310.06213 , 2023

Original

2023

Earlier work this paper cites.

W. Gurnee and M. Tegmark, “Language models represent space and time,” arXiv preprint arXiv:2310.02207 , 2023

Original

2023

Cited alongside, same era.

J. Roberts, T. Lüddecke, S. Das, K. Han, and S. Albanie, “Gpt4geo: How a language model sees the world’s geography,” arXiv preprint arXiv:2306.00020 , 2023

Original

2023

Cited alongside, same era.

X. Wang, M. Fang, Z. Zeng, and T. Cheng, “Where would i go next? large language models as human mobility predictors,” arXiv preprint arXiv:2308.15197 , 2023

Original

2023

Cited alongside, same era.

Z. Zhang, H. Amiri, Z. Liu, A. Züfle, and L. Zhao, “Large language models for spatial trajectory patterns mining,” arXiv preprint arXiv:2310.04942 , 2023

Original

2023

Cited alongside, same era.

Y. Liang, Y. Liu, X. Wang, and Z. Zhao, “Exploring large language models for human mobility prediction under public events,” arXiv preprint arXiv:2311.17351 , 2023

Z. Sun, Y. Lei, L. Zhang, C. Li, Y.-S. Ong, and J. Zhang, “A multi-channel next poi recommendation framework with multi-granularity check-in signals,” ACM Transactions on Information Systems , vol. 42, no. 1, pp. 1–28, 2023

2023

Later among the works it cites.

W. Fan, Z. Zhao, J. Li, Y. Liu, X. Mei, Y. Wang, J. Tang, and Q. Li, “Recommender systems in the era of large language models (llms),” arXiv preprint arXiv:2307.02046 , 2023

Original

2023

Later among the works it cites.

J. Li, W. Zhang, T. Wang, G. Xiong, A. Lu, and G. Medioni, “Gpt4rec: A generative framework for personalized recommendation and user interests interpretation,” arXiv preprint arXiv:2304.03879 , 2023

Original

2023

Later among the works it cites.

J. Harte, W. Zorgdrager, P. Louridas, A. Katsifodimos, D. Jannach, and M. Fragkoulis, “Leveraging large language models for sequential recommendation,” in Recsys , 2023, pp. 1096–1102

2023

Later among the works it cites.