{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T18:08:19Z","timestamp":1764698899335,"version":"3.46.0"},"publisher-location":"New York, NY, USA","reference-count":16,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,3]]},"DOI":"10.1145\/3764925.3770908","type":"proceedings-article","created":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T18:01:51Z","timestamp":1764698511000},"page":"22-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards Foundation Model-based Generation of Human Mobility Trajectories"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-0561-1738","authenticated-orcid":false,"given":"Siyu","family":"Li","sequence":"first","affiliation":[{"name":"Emory University, Atlanta, Georgia, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7524-5665","authenticated-orcid":false,"given":"Toan","family":"Tran","sequence":"additional","affiliation":[{"name":"Emory University, Atlanta, Georgia, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8544-3326","authenticated-orcid":false,"given":"Lingyi","family":"Zhao","sequence":"additional","affiliation":[{"name":"Novateur Research Solutions, Ashburn, Virginia, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3834-324X","authenticated-orcid":false,"given":"Khurram","family":"Shafique","sequence":"additional","affiliation":[{"name":"Novateur Research Solutions, Ashburn, Virginia, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7354-0428","authenticated-orcid":false,"given":"Li","family":"Xiong","sequence":"additional","affiliation":[{"name":"Emory University, Atlanta, Georgia, USA"}]}],"member":"320","published-online":{"date-parts":[[2025,12,2]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/3000850.3000887"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3678717.3691221"},{"key":"e_1_3_2_1_3_1","volume-title":"GPT-4-OSS: Open-Source 120B Parameter LLM. https:\/\/huggingface.co\/TheBloke\/GPT4-OSS- 120B. Accessed","author":"Community Open Source","year":"2025","unstructured":"Open Source Community. 2024. GPT-4-OSS: Open-Source 120B Parameter LLM. https:\/\/huggingface.co\/TheBloke\/GPT4-OSS- 120B. Accessed August 2025."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3690624.3709180"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3412862"},{"key":"e_1_3_2_1_6_1","volume-title":"LoRA: Low-Rank Adaptation of Large Language Models. In International Conference on Learning Representations (ICLR).","author":"Hu Edward J.","year":"2022","unstructured":"Edward J. Hu, Yelong Shen, Phil Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Lu Wang, and Weizhu Chen. 2022. LoRA: Low-Rank Adaptation of Large Language Models. In International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_7_1","first-page":"124547","article-title":"2024. Large language models as urban residents: An llm agent framework for personal mobility generation","volume":"37","author":"Renhe Jiang WANG JIAWEI","year":"2024","unstructured":"WANG JIAWEI, Renhe Jiang, Chuang Yang, Zengqing Wu, Ryosuke Shibasaki, Noboru Koshizuka, Chuan Xiao, et al. 2024. Large language models as urban residents: An llm agent framework for personal mobility generation. Advances in Neural Information Processing Systems 37 (2024), 124547--124574.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_8_1","volume-title":"Geo-Llama: Leveraging LLMs for Human Mobility Trajectory Generation with Constraints. In 2025 26th IEEE International Conference on Mobile Data Management (MDM). IEEE, 20--31","author":"Li Siyu","year":"2025","unstructured":"Siyu Li, Toan Tran, Haowen Lin, John Krumm, Cyrus Shahabi, Lingyi Zhao, Khurram Shafique, and Li Xiong. 2025. Geo-Llama: Leveraging LLMs for Human Mobility Trajectory Generation with Constraints. In 2025 26th IEEE International Conference on Mobile Data Management (MDM). IEEE, 20--31."},{"key":"e_1_3_2_1_9_1","volume-title":"Toolformer: Language Models Can Teach Themselves to Use Tools. In Advances in Neural Information Processing Systems.","author":"Schick Timo","year":"2023","unstructured":"Timo Schick, Jane Dwivedi-Yu, Roberto Dess\u00ec, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom. 2023. Toolformer: Language Models Can Teach Themselves to Use Tools. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_10_1","volume-title":"Agent AI with LangGraph: A Modular Framework for Enhancing Machine Translation Using Large Language Models. (2024). arXiv:2412.03801 arXiv preprint","author":"Wang Jialin","unstructured":"Jialin Wang and Zhihua Duan. 2024. Agent AI with LangGraph: A Modular Framework for Enhancing Machine Translation Using Large Language Models. (2024). arXiv:2412.03801 arXiv preprint; LangGraph framework for modular agent orchestration."},{"key":"e_1_3_2_1_11_1","volume-title":"Chi, Quoc Le, and Denny Zhou","author":"Wei Jason","year":"2022","unstructured":"Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou. 2022. Chain of Thought Prompting Elicits Reasoning in Large Language Models. In Advances in Neural Information Processing Systems. https:\/\/arxiv.org\/abs\/2201.11903"},{"key":"e_1_3_2_1_12_1","volume-title":"ReAct: Synergizing reasoning and acting in language models. arXiv preprint arXiv:2210.03629","author":"Yao Shinn","year":"2022","unstructured":"Shinn Yao, Jeffrey Yu, Jinxin Zhao, Karthik Narasimhan, Oren Etzioni, and Yejin Choi. 2022. ReAct: Synergizing reasoning and acting in language models. arXiv preprint arXiv:2210.03629 (2022)."},{"key":"e_1_3_2_1_13_1","unstructured":"Jianguo Zhang Tian Lan Ming Zhu Zuxin Liu and Caiming Xiong. 2024. xLAM: A Family of Large Action Models to Empower AI Agent Systems. (2024). arXiv:2409.03215 https:\/\/huggingface.co\/Salesforce\/Llama-xLAM-2-8b-fc-r."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/MDM58254.2023.00032"},{"key":"e_1_3_2_1_15_1","volume-title":"A Study on Individual Spatiotemporal Activity Generation Method Using MCP-Enhanced Chain-of-Thought Large Language Models. arXiv preprint arXiv:2506.10853","author":"Zhang Yu","year":"2025","unstructured":"Yu Zhang, Yang Hu, and De Wang. 2025. A Study on Individual Spatiotemporal Activity Generation Method Using MCP-Enhanced Chain-of-Thought Large Language Models. arXiv preprint arXiv:2506.10853 (2025)."},{"key":"e_1_3_2_1_16_1","unstructured":"Wayne Xin Zhao Kun Zhang Junlin Xie Jing Liu Zhicheng Li Yujie Shan Guocheng Yang Shuqing He Zhichun Wang Zhipeng Liu et al. 2023. A Survey of Large Language Models. arXiv preprint arXiv:2303.18223 (2023)."}],"event":{"name":"SIGSPATIAL '25: The 33rd ACM International Conference on Advances in Geographic Information Systems","location":"Minneapolis MN USA","acronym":"UMFM '25","sponsor":["SIGSPATIAL ACM Special Interest Group on Spatial Information"]},"container-title":["Proceedings of the 1st ACM SIGSPATIAL International Workshop on Urban Mobility Foundation Models"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3764925.3770908","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T18:02:15Z","timestamp":1764698535000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3764925.3770908"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,3]]},"references-count":16,"alternative-id":["10.1145\/3764925.3770908","10.1145\/3764925"],"URL":"https:\/\/doi.org\/10.1145\/3764925.3770908","relation":{},"subject":[],"published":{"date-parts":[[2025,11,3]]},"assertion":[{"value":"2025-12-02","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}