{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T07:04:06Z","timestamp":1776236646722,"version":"3.50.1"},"reference-count":36,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"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":["62276193"],"award-info":[{"award-number":["62276193"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Laboratory of Satellite Information Intelligent Processing and Application Technology","award":["2022-ZZKY-JJ-16-01"],"award-info":[{"award-number":["2022-ZZKY-JJ-16-01"]}]},{"name":"Joint Laboratory on Credit Science and Technology of China Securities Credit Investment (CSCI), Wuhan University"},{"name":"Supercomputing Center of Wuhan University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1109\/tnnls.2023.3258967","type":"journal-article","created":{"date-parts":[[2023,3,28]],"date-time":"2023-03-28T18:57:24Z","timestamp":1680029844000},"page":"11291-11301","source":"Crossref","is-referenced-by-count":7,"title":["Adversarial Multi-Teacher Distillation for Semi-Supervised Relation Extraction"],"prefix":"10.1109","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0670-5397","authenticated-orcid":false,"given":"Wanli","family":"Li","sequence":"first","affiliation":[{"name":"School of Computer Science, Wuhan University, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4667-5794","authenticated-orcid":false,"given":"Tieyun","family":"Qian","sequence":"additional","affiliation":[{"name":"School of Computer Science, Wuhan University, Wuhan, China"}]},{"given":"Xuhui","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Management, Wuhan University, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6755-871X","authenticated-orcid":false,"given":"Lixin","family":"Zou","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Engineering, Wuhan University, Wuhan, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3115\/1621969.1621986"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1074"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-016-0437-2"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/e17-1110"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10888-9_35"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313573"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-emnlp.44"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.164"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ACVMOT.2005.107"},{"key":"ref10","first-page":"1","article-title":"Self-ensembling for visual domain adaptation","volume-title":"Proc. 6th Int. Conf. Learn. Represent. (ICLR)","author":"French"},{"key":"ref11","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. Adv. Neural Inf. Process. Syst., Annu. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Tarvainen"},{"key":"ref12","first-page":"551","article-title":"Exploiting syntactico-semantic structures for relation extraction","volume-title":"Proc. Annu. Meeting Assoc. Comput. Linguistics (ACL)","author":"Chan"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1004"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3115\/1699648.1699684"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1279"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3115\/1690219.1690287"},{"key":"ref17","first-page":"288","article-title":"Coreference for learning to extract relations: Yes Virginia, coreference matters","volume-title":"Proc. Annu. Meeting Assoc. Comput. Linguistics (ACL)","author":"Gabbard"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s11390-012-1306-0"},{"key":"ref19","first-page":"172","article-title":"Minimising semantic drift with mutual exclusion bootstrapping","volume-title":"Proc. PACLING","author":"Curran"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1503.02531"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00454"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1595"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i14.17518"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6509"},{"key":"ref25","first-page":"1","article-title":"Explaining and harnessing adversarial examples","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Goodfellow"},{"key":"ref26","first-page":"1","article-title":"Intriguing properties of neural networks","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Szegedy"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5816"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7503.003.0080"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1203"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1024"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.523"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"key":"ref33","article-title":"SemEval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals","author":"Hendrickx","year":"2019","journal-title":"arXiv:1911.10422"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380282"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5963"},{"key":"ref36","first-page":"6391","article-title":"Visualizing the loss landscape of neural nets","volume-title":"Proc. Adv. Neural Inf. Process. Syst., Annu. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Li"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/10623582\/10083156.pdf?arnumber=10083156","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T10:22:12Z","timestamp":1722939732000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10083156\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":36,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2023.3258967","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8]]}}}