{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T18:05:04Z","timestamp":1764698704127,"version":"3.46.0"},"publisher-location":"New York, NY, USA","reference-count":26,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,3]]},"DOI":"10.1145\/3764925.3770911","type":"proceedings-article","created":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T18:01:51Z","timestamp":1764698511000},"page":"10-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Capturing Shared and Unique Information in Multimodal Region Representations for Urban Mobility Prediction"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0933-5117","authenticated-orcid":false,"given":"Min","family":"Namgung","sequence":"first","affiliation":[{"name":"University of Minnesota, Minneapolis, Minnesota, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4447-3697","authenticated-orcid":false,"given":"JangHyeon","family":"Lee","sequence":"additional","affiliation":[{"name":"University of Minnesota, Minneapolis, Minnesota, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0815-9636","authenticated-orcid":false,"given":"Yijun","family":"Lin","sequence":"additional","affiliation":[{"name":"University of Minnesota, Minneapolis, Minnesota, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8923-0130","authenticated-orcid":false,"given":"Yao-Yi","family":"Chiang","sequence":"additional","affiliation":[{"name":"University of Minnesota, Minneapolis, Minnesota, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,12,2]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Proceedings of the 37th International Conference on Machine Learning (Proceedings of Machine Learning Research","author":"Chen Ting","year":"2020","unstructured":"Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020. A Simple Framework for Contrastive Learning of Visual Representations. In Proceedings of the 37th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 119), Hal Daum\u00e9 III and Aarti Singh (Eds.). PMLR, 1597--1607."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2025.103265"},{"key":"e_1_3_2_1_3_1","volume-title":"International conference on machine learning. PMLR, 1779--1788","author":"Cheng Pengyu","year":"2020","unstructured":"Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, and Lawrence Carin. 2020. Club: A contrastive log-ratio upper bound of mutual information. In International conference on machine learning. PMLR, 1779--1788."},{"key":"e_1_3_2_1_4_1","unstructured":"City of New York. 2025. CommonPlace - City of New York Open Data. https:\/\/data.cityofnewyork.us\/City-Government\/CommonPlace\/rxuy-2muj."},{"key":"e_1_3_2_1_5_1","unstructured":"Geofabrik GmbH. 2025. Geofabrik Download Server. https:\/\/download.geofabrik.de\/."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599538"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i8.28718"},{"key":"e_1_3_2_1_9_1","unstructured":"Paul Pu Liang Zihao Deng Martin Ma James Zou Louis-Philippe Morency and Ruslan Salakhutdinov. 2023. Factorized Contrastive Learning: Going Beyond Multi-view Redundancy. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2023.104241"},{"key":"e_1_3_2_1_11_1","volume-title":"Self-supervised learning: Generative or contrastive","author":"Liu Xiao","year":"2021","unstructured":"Xiao Liu, Fanjin Zhang, Zhenyu Hou, Li Mian, Zhaoyu Wang, Jing Zhang, and Jie Tang. 2021. Self-supervised learning: Generative or contrastive. IEEE transactions on knowledge and data engineering 35, 1 (2021), 857--876."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583876"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.3390\/en16083585"},{"key":"e_1_3_2_1_14_1","volume-title":"Fangyi Ding, and Yao-Yi Chiang.","author":"Namgung Min","year":"2025","unstructured":"Min Namgung, Jang Hyeon Lee, Fangyi Ding, and Yao-Yi Chiang. 2025. Transit for All: Mapping Equitable Bike2Subway Connection using Region Representation Learning. arXiv preprint arXiv:2506.15113 (2025)."},{"key":"e_1_3_2_1_15_1","volume-title":"Less is More: Multimodal Region Representation via Pairwise Inter-view Learning. arXiv preprint arXiv:2505.18178","author":"Namgung Min","year":"2025","unstructured":"Min Namgung, Yijun Lin, JangHyeon Lee, and Yao-Yi Chiang. 2025. Less is More: Multimodal Region Representation via Pairwise Inter-view Learning. arXiv preprint arXiv:2505.18178 (2025)."},{"key":"e_1_3_2_1_16_1","unstructured":"New York State. 2025. MTA Subway Stations - New York State Open Data. https:\/\/data.ny.gov\/Transportation\/MTA-Subway-Stations\/39hk-dx4f\/about_data."},{"key":"e_1_3_2_1_17_1","volume-title":"Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748","author":"van den Oord Aaron","year":"2018","unstructured":"Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748 (2018)."},{"key":"e_1_3_2_1_18_1","volume-title":"International conference on machine learning. PMLR, 8748--8763","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021. Learning transferable visual models from natural language supervision. In International conference on machine learning. PMLR, 8748--8763."},{"key":"e_1_3_2_1_19_1","volume-title":"Mobility and aging: new directions for public health action. American journal of public health 102, 8","author":"Satariano William A","year":"2012","unstructured":"William A Satariano, Jack M Guralnik, Richard J Jackson, Richard A Marottoli, Elizabeth A Phelan, and Thomas R Prohaska. 2012. Mobility and aging: new directions for public health action. American journal of public health 102, 8 (2012), 1508--1515."},{"key":"e_1_3_2_1_20_1","unstructured":"Yonglong Tian Chen Sun Ben Poole Dilip Krishnan Cordelia Schmid and Phillip Isola. 2020. What makes for good views for contrastive learning? Advances in neural information processing systems 33 6827--6839."},{"key":"e_1_3_2_1_21_1","unstructured":"United States Department of Agriculture. 2021. National Agriculture Imagery Program (NAIP). https:\/\/naip-usdaonline.hub.arcgis.com\/."},{"key":"e_1_3_2_1_22_1","unstructured":"U.S. Census Bureau. 2025. Census Bureau Datasets. https:\/\/www.census.gov\/data\/datasets.html."},{"key":"e_1_3_2_1_23_1","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 16041--16050","author":"Wang Haoqing","year":"2022","unstructured":"Haoqing Wang, Xun Guo, Zhi-Hong Deng, and Yan Lu. 2022. Rethinking minimal sufficient representation in contrastive learning. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 16041--16050."},{"key":"e_1_3_2_1_24_1","volume-title":"2017 18th IEEE International Conference on Mobile Data Management (MDM). IEEE, 266--271","author":"Wang Zhaoyang","year":"2017","unstructured":"Zhaoyang Wang, Beihong Jin, Fusang Zhang, Ruiyang Yang, and Qiang Ji. 2017. Exploiting trip patterns in passenger trajectory streams for bus scheduling optimization in real time. In 2017 18th IEEE International Conference on Mobile Data Management (MDM). IEEE, 266--271."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3220874"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671453"}],"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\/3764925.3770911","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T18:01:54Z","timestamp":1764698514000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3764925.3770911"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,3]]},"references-count":26,"alternative-id":["10.1145\/3764925.3770911","10.1145\/3764925"],"URL":"https:\/\/doi.org\/10.1145\/3764925.3770911","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"}}]}}