{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T12:20:42Z","timestamp":1767183642620,"version":"3.44.0"},"reference-count":40,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62306033","42371480"],"award-info":[{"award-number":["62306033","42371480"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Big Data"],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1109\/tbdata.2024.3524083","type":"journal-article","created":{"date-parts":[[2024,12,30]],"date-time":"2024-12-30T14:37:55Z","timestamp":1735569475000},"page":"2264-2277","source":"Crossref","is-referenced-by-count":5,"title":["FinLLMs: A Framework for Financial Reasoning Dataset Generation With Large Language Models"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-2309-1721","authenticated-orcid":false,"given":"Ziqiang","family":"Yuan","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5375-3757","authenticated-orcid":false,"given":"Kaiyuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Central University of Finance and Economics, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8546-0099","authenticated-orcid":false,"given":"Shoutai","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0247-9866","authenticated-orcid":false,"given":"Ye","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0721-7424","authenticated-orcid":false,"given":"Jingya","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Soochow University, Suzhou, China"}]},{"given":"Yanlin","family":"Zhu","sequence":"additional","affiliation":[{"name":"Moody&#x0027;s Analytics, New York, NY, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9177-114X","authenticated-orcid":false,"given":"Wenqi","family":"Wei","sequence":"additional","affiliation":[{"name":"Computer and Information Science Department, Fordham University, New York, NY, USA"}]}],"member":"263","reference":[{"article-title":"Multi-view graph representation learning for answering hybrid numerical reasoning question","year":"2023","author":"Wei","key":"ref1"},{"key":"ref2","first-page":"1379","article-title":"Answering numerical reasoning questions in table-text hybrid contents with graph-based encoder and tree-based decoder","volume-title":"Proc. Int. Conf. Comput. Linguistics","author":"Lei"},{"volume-title":"Principles of Accounting","year":"2013","author":"Needles","key":"ref3"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.300"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.254"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i11.26543"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"article-title":"RoBERTa: A robustly optimized BERT pretraining approach","year":"2019","author":"Liu","key":"ref8"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.454"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i11.26529"},{"key":"ref11","first-page":"2368","article-title":"DROP: A reading comprehension benchmark requiring discrete reasoning over paragraphs","volume-title":"Proc. Conf. North Amer. Chapter Assoc. Comput. Linguistics: Hum. Lang. Technol. Assoc. Comput. Linguistics","author":"Dua"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/SCOPES.2016.7955659"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1183"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-4007"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1620"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.340"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-015-0564-6"},{"article-title":"TabFact: A large-scale dataset for table-based fact verification","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Chen","key":"ref18"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.91"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3560260"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.14778\/3231751.3231757"},{"key":"ref22","first-page":"7333","article-title":"Modeling tabular data using conditional GAN","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Xu"},{"key":"ref23","first-page":"97","article-title":"CTAB-GAN: Effective table data synthesizing","volume-title":"Proc. Asian Conf. Mach. Learn.","author":"Zhao"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/PRDC47002.2019.00050"},{"article-title":"Synthesising multi-modal minority samples for tabular data","year":"2021","author":"Darabi","key":"ref25"},{"article-title":"Language models are realistic tabular data generators","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Borisov","key":"ref26"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548422"},{"article-title":"Bizbench: A. quantitative reasoning benchmark for business and finance","year":"2023","author":"Koncel-Kedziorski","key":"ref28"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.acl-long.693"},{"key":"ref30","first-page":"17564","article-title":"TabDDPM: Modelling tabular data with diffusion models","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Kotelnikov"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-78139-4_22"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6410"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.421"},{"key":"ref34","first-page":"1125","article-title":"Generating questions and multiple-choice answers using semantic analysis of texts","volume-title":"Proc. Int. Conf. Comput. Linguistics","author":"Araki"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3543873.3587598"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3604237.3626902"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3604237.3626869"},{"key":"ref38","first-page":"2357","article-title":"MathQA: Towards interpretable math word problem solving with operation-based formalisms","volume-title":"Proc. 2019 Conf. North Amer. Chapter Assoc. Comput. Linguistics","author":"Amini"},{"year":"2024","key":"ref39","article-title":"Llama 3 model card"},{"article-title":"Using large language model to solve and explain physics word problems approaching human level","year":"2023","author":"Ding","key":"ref40"}],"container-title":["IEEE Transactions on Big Data"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6687317\/11149634\/10818583.pdf?arnumber=10818583","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,4]],"date-time":"2025-09-04T04:37:23Z","timestamp":1756960643000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10818583\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10]]},"references-count":40,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tbdata.2024.3524083","relation":{},"ISSN":["2332-7790","2372-2096"],"issn-type":[{"type":"electronic","value":"2332-7790"},{"type":"electronic","value":"2372-2096"}],"subject":[],"published":{"date-parts":[[2025,10]]}}}