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Federated Transfer Learning (FTL), the combination of federated learning and transfer learning, provides promising solutions to address these challenges. Recently, the need for grounding FMs leveraging FTL, coined FTL-FM, has arisen strongly in both academia and industry. Motivated by the strong growth in FTL-FM research and the potential impact of FTL-FM on industrial applications, we propose an FTL-FM framework that formulates problems of grounding FMs in the federated learning setting, construct a detailed taxonomy based on the FTL-FM framework to categorize state-of-the-art FTL-FM works, and comprehensively overview FTL-FM works based on the proposed taxonomy. We also establish correspondence between FTL-FM and conventional phases of adapting FM so that FM practitioners can align their research works with FTL-FM. In addition, we overview advanced efficiency-improving and privacy-preserving techniques because efficiency and privacy are critical concerns in FTL-FM. Last, we discuss opportunities and future research directions of FTL-FM.<\/jats:p>","DOI":"10.1145\/3742788","type":"journal-article","created":{"date-parts":[[2025,6,5]],"date-time":"2025-06-05T10:23:13Z","timestamp":1749118993000},"page":"1-54","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Grounding Foundation Models through Federated Transfer Learning: A General Framework"],"prefix":"10.1145","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2016-9503","authenticated-orcid":false,"given":"Yan","family":"Kang","sequence":"first","affiliation":[{"name":"WeBank, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3040-6140","authenticated-orcid":false,"given":"Tao","family":"Fan","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8266-4561","authenticated-orcid":false,"given":"Hanlin","family":"Gu","sequence":"additional","affiliation":[{"name":"WeBank, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9065-6852","authenticated-orcid":false,"given":"Xiaojin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8162-7096","authenticated-orcid":false,"given":"Lixin","family":"Fan","sequence":"additional","affiliation":[{"name":"WeBank, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5059-8360","authenticated-orcid":false,"given":"Qiang","family":"Yang","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,8,18]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.393"},{"key":"e_1_3_2_4_2","volume-title":"International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS 2023","author":"Azam Sheikh Shams","year":"2023","unstructured":"Sheikh Shams Azam, Martin Pelikan, Vitaly Feldman, Kunal Talwar, Jan Silovsky, and Tatiana Likhomanenko. 2023. 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