{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T22:25:34Z","timestamp":1776378334311,"version":"3.51.2"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"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":["62076217"],"award-info":[{"award-number":["62076217"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62120106008"],"award-info":[{"award-number":["62120106008"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Language Commission of China","award":["ZDI145-71"],"award-info":[{"award-number":["ZDI145-71"]}]},{"name":"Key Research and Development Program of Jiangsu Province in China","award":["BE2023315"],"award-info":[{"award-number":["BE2023315"]}]},{"name":"Yangzhou Science and Technology Plan Project City School Cooperation Special Project","award":["YZ2023199"],"award-info":[{"award-number":["YZ2023199"]}]},{"name":"Open Project of Anhui Provincial Key Laboratory for Intelligent Manufacturing of Construction Machinery","award":["IMCM-2023-01"],"award-info":[{"award-number":["IMCM-2023-01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1109\/tkde.2024.3483903","type":"journal-article","created":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T17:23:09Z","timestamp":1729531389000},"page":"8580-8592","source":"Crossref","is-referenced-by-count":1,"title":["Iterative Soft Prompt-Tuning for Unsupervised Domain Adaptation"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3045-2588","authenticated-orcid":false,"given":"Yi","family":"Zhu","sequence":"first","affiliation":[{"name":"Department of Information Engineering, Yangzhou University, Yangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-6182-4413","authenticated-orcid":false,"given":"Shuqin","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Yangzhou University, Yangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5721-0293","authenticated-orcid":false,"given":"Jipeng","family":"Qiang","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Yangzhou University, Yangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2396-1704","authenticated-orcid":false,"given":"Xindong","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Knowledge Engineering with Big Data, Ministry of Education of China, Hefei University of Technology, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3014697"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW60793.2023.00468"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2022.3167013"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/587"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3230825"},{"key":"ref6","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018"},{"key":"ref7","article-title":"RoBERTa: A robustly optimized BERT pretraining approach","author":"Liu","year":"2019"},{"issue":"1","key":"ref8","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":"ref9","first-page":"1877","article-title":"Language models are few-shot learners","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Brown"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511998"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.292"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2022.11.003"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2023.3327962"},{"key":"ref14","article-title":"SPoT: Better frozen model adaptation through soft prompt transfer","author":"Vu","year":"2021"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.174"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s11704-022-1349-5"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-021-3535-2"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3115\/1610075.1610094"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2091281"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2824309"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2554549"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/285"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.03.056"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.5555\/2946645.2946704"},{"key":"ref25","article-title":"Conditional generative adversarial nets","author":"Mirza","year":"2014"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"ref27","article-title":"Assessing BERT\u2019s syntactic abilities","author":"Goldberg","year":"2019"},{"key":"ref28","article-title":"Universal text representation from BERT: An empirical study","author":"Ma","year":"2019"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1356"},{"key":"ref30","article-title":"Incorporating bert into neural machine translation","author":"Zhu","year":"2020"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6465"},{"issue":"3","key":"ref32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3439726","article-title":"Deep learning\u2013based text classification: A comprehensive review","volume":"54","author":"Minaee","year":"2021","journal-title":"ACM Comput. Surv."},{"key":"ref33","article-title":"Prototypical representation learning for relation extraction","author":"Ding","year":"2021"},{"key":"ref34","article-title":"Data augmentation for BERT fine-tuning in open-domain question answering","author":"Yang","year":"2019"},{"key":"ref35","article-title":"Towards a human-like open-domain chatbot","author":"Adiwardana","year":"2020"},{"key":"ref36","article-title":"Enhancing pre-trained language model with lexical simplification","author":"Bao","year":"2020"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6389"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-6109"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2022.102964"},{"key":"ref40","article-title":"GPT understands, too","author":"Liu","year":"2021"},{"key":"ref41","article-title":"Sentiprompt: Sentiment knowledge enhanced prompt-tuning for aspect-based sentiment analysis","author":"Li","year":"2021"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.coling-main.488"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.243"},{"key":"ref44","article-title":"P-tuning v2: Prompt tuning can be comparable to fine-tuning universally across scales and tasks","author":"Liu","year":"2021"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.295"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-15931-2_19"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.158"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00608"},{"key":"ref49","first-page":"3833","article-title":"Rethinking pre-training and self-training","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zoph"},{"key":"ref50","article-title":"Self-training: A survey","author":"Amini","year":"2022"},{"key":"ref51","first-page":"1","article-title":"Temporal ensembling for semi-supervised learning","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Laine"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115002"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i15.29611"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/d14-1181"},{"key":"ref55","first-page":"513","article-title":"Domain adaptation for large-scale sentiment classification: A deep learning approach","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Glorot"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-demo.10"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/69\/10750897\/10723770.pdf?arnumber=10723770","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T01:08:33Z","timestamp":1732669713000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10723770\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12]]},"references-count":56,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2024.3483903","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12]]}}}