{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T20:45:17Z","timestamp":1775594717254,"version":"3.50.1"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Big Data"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1109\/tbdata.2025.3536934","type":"journal-article","created":{"date-parts":[[2025,1,30]],"date-time":"2025-01-30T19:23:41Z","timestamp":1738265021000},"page":"907-918","source":"Crossref","is-referenced-by-count":69,"title":["AugGPT: Leveraging ChatGPT for Text Data Augmentation"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0409-6129","authenticated-orcid":false,"given":"Haixing","family":"Dai","sequence":"first","affiliation":[{"name":"School of Computing, University of Georgia, Athens, GA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7061-6714","authenticated-orcid":false,"given":"Zhengliang","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computing, University of Georgia, Athens, GA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9432-9426","authenticated-orcid":false,"given":"Wenxiong","family":"Liao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"}]},{"given":"Xiaoke","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"}]},{"given":"Yihan","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7483-6570","authenticated-orcid":false,"given":"Zihao","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computing, University of Georgia, Athens, GA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2567-627X","authenticated-orcid":false,"given":"Lin","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computing, University of Georgia, Athens, GA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-0802-9218","authenticated-orcid":false,"given":"Shaochen","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computing, University of Georgia, Athens, GA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7472-3194","authenticated-orcid":false,"given":"Fang","family":"Zeng","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0935-3999","authenticated-orcid":false,"given":"Wei","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9170-2424","authenticated-orcid":false,"given":"Ninghao","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computing, University of Georgia, Athens, GA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1205-8632","authenticated-orcid":false,"given":"Sheng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Data Science, University of Virginia, Charlottesville, VA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6940-3911","authenticated-orcid":false,"given":"Dajiang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2747-7234","authenticated-orcid":false,"given":"Hongmin","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1539-7939","authenticated-orcid":false,"given":"Lichao","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9651-5820","authenticated-orcid":false,"given":"Quanzheng","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7934-5698","authenticated-orcid":false,"given":"Dinggang","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8132-9048","authenticated-orcid":false,"given":"Tianming","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computing, University of Georgia, Athens, GA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9851-6376","authenticated-orcid":false,"given":"Xiang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3386252"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.221"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.naacl-main.49"},{"key":"ref4","first-page":"1877","article-title":"Language models are few-shot learners","volume-title":"Proc. Adv. Neural Info. Process. Syst.","author":"Brown"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-6101"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.coling-main.611"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3544558"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/rbme.2024.3493775"},{"key":"ref9","first-page":"27730","article-title":"Training language models to follow instructions with human feedback","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ouyang"},{"key":"ref10","article-title":"Synthetic and natural noise both break neural machine translation","author":"Belinkov","year":"2017"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1670"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/K18-1047"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1306"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1310.4546"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d18-1316"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-2072"},{"issue":"2","key":"ref17","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","volume-title":"Proc. NAACcl-HLT","volume":"1","author":"Kenton","year":"2019"},{"key":"ref18","article-title":"DistilBERT, a distilled version of BERT: Smaller, faster, cheaper and lighter","author":"Sanh","year":"2019"},{"key":"ref19","article-title":"RoBERTa: A robustly optimized BERT pretraining approach","author":"Liu","year":"2019"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-1009"},{"key":"ref21","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Finn"},{"key":"ref22","article-title":"Improving language understanding by generative pre-training","author":"Radford","year":"2018"},{"issue":"1","key":"ref23","first-page":"5485","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","volume":"21","author":"Raffel","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref24","article-title":"BLOOM: A 176B-parameter open-access multilingual language model","author":"Scao","year":"2022"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-21014-3_28"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.85"},{"key":"ref27","article-title":"Is chatGPT a good translator? A preliminary study","author":"Jiao","year":"2023"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.ijcnlp-main.45"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TAI.2024.3364586"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-45673-2_46"},{"key":"ref31","article-title":"Reasoning before comparison: LLM-enhanced semantic similarity metrics for domain specialized text analysis","author":"Xu","year":"2024"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pdig.0000198"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.frl.2023.103662"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1038\/d41586-023-00288-7"},{"key":"ref35","first-page":"187","article-title":"Co-authoring with an AI? Ethical dilemmas and artificial intelligence","volume":"56","author":"Jabotinsky","year":"2024","journal-title":"Ariz. St. LJ."},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.2196\/48904"},{"key":"ref37","article-title":"MedEdit: Model editing for medical question answering with external knowledge bases","author":"Shi","year":"2023"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW60847.2023.00073"},{"key":"ref39","article-title":"TrustLLM: Trustworthiness in large language models","author":"Sun","year":"2024"},{"key":"ref40","first-page":"4844","article-title":"Sentence-aware adversarial meta-learning for few-shot text classification","volume-title":"Proc. 29th Int. Conf. Comput. Linguistics","author":"Wang"},{"key":"ref41","first-page":"4171","volume-title":"Proc. Conf. North Amer. Chapter Assoc. Comput. Linguistics - Hum. Lang. Technol.","author":"Devlin"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128576"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/219717.219748"},{"key":"ref44","article-title":"NLP augmentation","author":"Ma","year":"2019"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/w19-5333"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/cvprw56347.2022.00027"},{"key":"ref47","first-page":"9201","article-title":"Frustratingly easy transferability estimation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Huang"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.733"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-demos.16"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.3389\/fradi.2023.1224682"}],"container-title":["IEEE Transactions on Big Data"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6687317\/11003987\/10858342.pdf?arnumber=10858342","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,15]],"date-time":"2025-05-15T19:37:20Z","timestamp":1747337840000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10858342\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6]]},"references-count":50,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tbdata.2025.3536934","relation":{},"ISSN":["2332-7790","2372-2096"],"issn-type":[{"value":"2332-7790","type":"electronic"},{"value":"2372-2096","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6]]}}}