{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T14:17:33Z","timestamp":1762957053840,"version":"3.28.0"},"reference-count":34,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,8,21]],"date-time":"2022-08-21T00:00:00Z","timestamp":1661040000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,8,21]],"date-time":"2022-08-21T00:00:00Z","timestamp":1661040000000},"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":[],"published-print":{"date-parts":[[2022,8,21]]},"DOI":"10.1109\/icpr56361.2022.9956208","type":"proceedings-article","created":{"date-parts":[[2022,11,29]],"date-time":"2022-11-29T19:34:13Z","timestamp":1669750453000},"page":"2935-2941","source":"Crossref","is-referenced-by-count":3,"title":["Shuffle &amp; Divide: Contrastive Learning for Long Text"],"prefix":"10.1109","author":[{"given":"Joonseok","family":"Lee","sequence":"first","affiliation":[{"name":"Samsung SDS,Seoul,South Korea"}]},{"given":"Seongho","family":"Joe","sequence":"additional","affiliation":[{"name":"Samsung SDS,Seoul,South Korea"}]},{"given":"Kyoungwon","family":"Park","sequence":"additional","affiliation":[{"name":"Samsung SDS,Seoul,South Korea"}]},{"given":"Bogun","family":"Kim","sequence":"additional","affiliation":[{"name":"Samsung SDS,Seoul,South Korea"}]},{"given":"Hoyoung","family":"Kang","sequence":"additional","affiliation":[{"name":"Samsung SDS,Seoul,South Korea"}]},{"given":"Jaeseon","family":"Park","sequence":"additional","affiliation":[{"name":"Samsung SDS,Seoul,South Korea"}]},{"given":"Youngjune","family":"Gwon","sequence":"additional","affiliation":[{"name":"Samsung SDS,Seoul,South Korea"}]}],"member":"263","reference":[{"key":"ref33","article-title":"Integrating document clustering and topic modeling","volume":"abs 1309 6874","author":"xie","year":"2013","journal-title":"ArXiv"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007612920971"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1169"},{"key":"ref30","first-page":"361","article-title":"Rcv1: A new benchmark collection for text categorization research","volume":"5","author":"lewis","year":"2004","journal-title":"J Mach Learn Res"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1002\/nav.3800020109"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.167"},{"key":"ref11","article-title":"Colorful image colorization","author":"zhang","year":"2016","journal-title":"European Conference on Computer Vision (ECCV)"},{"key":"ref12","article-title":"Unsupervised learning of visual representations by solving jigsaw puzzles","author":"noroozi","year":"2016","journal-title":"European Conference on Computer Vision (ECCV)"},{"key":"ref13","article-title":"Unsupervised representation learning by predicting image rotations","author":"gidaris","year":"2018","journal-title":"International Conference on Learning Representations (ICLR)"},{"key":"ref14","article-title":"On mutual information maximization for representation learning","author":"tschannen","year":"2020","journal-title":"International Conference on Learning Representations (ICLR)"},{"key":"ref15","article-title":"Representation learning with contrastive predictive coding","author":"oord","year":"2018","journal-title":"arXiv preprint arXiv 1807 03748"},{"key":"ref16","article-title":"Learning deep representations by mutual information estimation and maximization","author":"hjelm","year":"2019","journal-title":"International Conference on Learning Representations (ICLR)"},{"key":"ref17","article-title":"Learning representations by maximizing mutual information across views","author":"bachman","year":"2019","journal-title":"Advances in Neural IInformation Processing Systems"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref19","article-title":"Language models are few-shot learners","author":"brown","year":"2020","journal-title":"arXiv preprint arXiv 2005 14354"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1410"},{"key":"ref4","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","author":"chen","year":"2020","journal-title":"International Conference on Machine Learning"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"2227","DOI":"10.18653\/v1\/N18-1202","article-title":"Deep contextualized word representations","author":"peters","year":"2018","journal-title":"Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics Human Language Technologies Volume 1 (Long Papers)"},{"key":"ref3","article-title":"Albert: A lite bert for self-supervised learning of language representations","author":"lan","year":"2019","journal-title":"arXiv preprint arXiv 1909 11324"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01210"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/B978-1-55860-377-6.50048-7"},{"key":"ref5","first-page":"268","article-title":"Scan: Learning to classify images without labels","author":"van gansbeke","year":"2020","journal-title":"European Conference on Computer Vision"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.32"},{"key":"ref7","article-title":"Self-match: Combining contrastive self-supervision and consistency for semi-supervised learning","author":"kim","year":"2021","journal-title":"arXiv preprint arXiv 2101 06286"},{"key":"ref2","article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2019","journal-title":"NAACL"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.366"},{"key":"ref1","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref20","article-title":"Semi-supervised sequence learning","author":"dai","year":"2015","journal-title":"NIPS"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1045"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1670"},{"key":"ref24","first-page":"986","author":"sammut","year":"2010","journal-title":"tf&#x2013;idf"},{"key":"ref23","first-page":"18","article-title":"Data augmentation using pre-trained transformer models","author":"kumar","year":"2020","journal-title":"Proceedings of the 2nd Workshop on Life-long Learning for Spoken Language Systems"},{"key":"ref26","first-page":"993","article-title":"Latent dirichlet allocation","volume":"3","author":"blei","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/275487.275505"}],"event":{"name":"2022 26th International Conference on Pattern Recognition (ICPR)","start":{"date-parts":[[2022,8,21]]},"location":"Montreal, QC, Canada","end":{"date-parts":[[2022,8,25]]}},"container-title":["2022 26th International Conference on Pattern Recognition (ICPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9956007\/9955631\/09956208.pdf?arnumber=9956208","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T20:03:59Z","timestamp":1671480239000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9956208\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,21]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/icpr56361.2022.9956208","relation":{},"subject":[],"published":{"date-parts":[[2022,8,21]]}}}