Deciphering Human Mobility: Inferring Semantics of Trajectories with Large Language Models

R. Kitamura, “An evaluation of activity-based travel analysis,” Transportation , vol. 15, pp. 9–34, 1988

1988

Earlier work this paper cites.

J. L. Bowman and M. E. Ben-Akiva, “Activity-based disaggregate travel demand model system with activity schedules,” Transportation research part a: policy and practice , vol. 35, no. 1, pp. 1–28, 2001

2001

Earlier work this paper cites.

N. C. McDonald, “Critical factors for active transportation to school among low-income and minority students: evidence from the 2001 national household travel survey,” American journal of preventive medicine , vol. 34, no. 4, pp. 341–344, 2008

2008

Earlier work this paper cites.

J. Yuan, Y. Zheng, X. Xie, and G. Sun, “T-drive: Enhancing driving directions with taxi drivers’ intelligence,” IEEE Transactions on Knowledge and Data Engineering , vol. 25, no. 1, pp. 220–232, 2011

2011

Earlier work this paper cites.

J. Yuan, Y. Zheng, and X. Xie, “Discovering regions of different functions in a city using human mobility and pois,” in Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining , 2012, pp. 186–194

2012

Earlier work this paper cites.

P. Widhalm, Y. Yang, M. Ulm, S. Athavale, and M. C. González, “Discovering urban activity patterns in cell phone data,” Transportation , vol. 42, pp. 597–623, 2015

2015

Earlier work this paper cites.

M. Diao, Y. Zhu, J. Ferreira Jr, and C. Ratti, “Inferring individual daily activities from mobile phone traces: A boston example,” Environment and Planning B: Planning and Design , vol. 43, no. 5, pp. 920–940, 2016

2016

Earlier work this paper cites.

L. Gong, X. Liu, L. Wu, and Y. Liu, “Inferring trip purposes and uncovering travel patterns from taxi trajectory data,” Cartography and Geographic Information Science , vol. 43, no. 2, pp. 103–114, 2016

2016

Earlier work this paper cites.

M. Yin, M. Sheehan, S. Feygin, J.-F. Paiement, and A. Pozdnoukhov, “A generative model of urban activities from cellular data,” IEEE Transactions on Intelligent Transportation Systems , vol. 19, no. 6, pp. 1682–1696, 2017

2017

Cited alongside, same era.

Y. Zhang and L. Liu, “Understanding temporal pattern of human activities using temporal areas of interest,” Applied geography , vol. 94, pp. 95–106, 2018

2018

Cited alongside, same era.

J. Wang, L. Dong, X. Cheng, W. Yang, and Y. Liu, “An extended exploration and preferential return model for human mobility simulation at individual and collective levels,” Physica A: Statistical Mechanics and Its Applications , vol. 534, p. 121921, 2019

2019

Cited alongside, same era.

X. Yang, Z. Fang, L. Yin, J. Li, S. Lu, and Z. Zhao, “Revealing the relationship of human convergence–divergence patterns and land use: A case study on shenzhen city, china,” Cities , vol. 95, p. 102384, 2019

2019

Cited alongside, same era.

J. Wei, X. Wang, D. Schuurmans, M. Bosma, F. Xia, E. Chi, Q. V. Le, D. Zhou et al. , “Chain-of-thought prompting elicits reasoning in large language models,” Advances in neural information processing systems , vol. 35, pp. 24 824–24 837, 2022

2022

Later among the works it cites.

J. Achiam, S. Adler, S. Agarwal, L. Ahmad, I. Akkaya, F. L. Aleman, D. Almeida, J. Altenschmidt, S. Altman, S. Anadkat et al. , “Gpt-4 technical report,” arXiv preprint arXiv:2303.08774 , 2023

Original

2023

Later among the works it cites.

G. Team, R. Anil, S. Borgeaud, Y. Wu, J.-B. Alayrac, J. Yu, R. Soricut, J. Schalkwyk, A. M. Dai, A. Hauth et al. , “Gemini: a family of highly capable multimodal models,” arXiv preprint arXiv:2312.11805 , 2023

Original

2023

Later among the works it cites.

H. Touvron, T. Lavril, G. Izacard, X. Martinet, M.-A. Lachaux, T. Lacroix, B. Rozière, N. Goyal, E. Hambro, F. Azhar et al. , “Llama: Open and efficient foundation language models,” arXiv preprint arXiv:2302.13971 , 2023

Original

2023