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TabulaX first classifies input columns into four transformation types\u2014string-based, numerical, algorithmic, and general\u2014and then applies tailored methods to generate human-interpretable transformation functions, such as numeric formulas or programming code. This approach enhances transparency and allows users to understand and modify the mappings. Through extensive experiments on real-world datasets from various domains, we demonstrate that TabulaX outperforms existing state-of-the-art approaches in terms of accuracy, supports a broader class of transformations, and generates interpretable transformations that can be efficiently applied.<\/jats:p>","DOI":"10.14778\/3749646.3749657","type":"journal-article","created":{"date-parts":[[2025,9,4]],"date-time":"2025-09-04T17:55:06Z","timestamp":1757008506000},"page":"3826-3839","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["TabulaX: Leveraging Large Language Models for Multi-Class Table Transformations"],"prefix":"10.14778","volume":"18","author":[{"given":"Arash Dargahi","family":"Nobari","sequence":"first","affiliation":[{"name":"University of Alberta, Edmonton, AB, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Davood","family":"Rafiei","sequence":"additional","affiliation":[{"name":"University of Alberta, Edmonton, AB, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,9,4]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2016.7498319"},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 3786\u20133790","author":"Rastaghi Mehdi Akbarian","year":"2022","unstructured":"Mehdi Akbarian Rastaghi, Ehsan Kamalloo, and Davood Rafiei. 2022. 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