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To address these challenges, we present CAMEL (Confidence-based Acquisition Model for Efficient self-supervised active Learning), a pool-based active learning framework tailored to sequential multi-output problems. CAMEL possesses two core features: (1) it requires expert annotators to label only a fraction of a chosen sequence, and (2) it facilitates self-supervision for the remainder of the sequence. By deploying a label correction mechanism, CAMEL can also be utilized for data cleaning. We evaluate CAMEL on two sequential tasks, with a special emphasis on dialogue belief tracking, a task plagued by the constraints of limited and noisy datasets. Our experiments demonstrate that CAMEL significantly outperforms the baselines in terms of efficiency. Furthermore, the data corrections suggested by our method contribute to an overall improvement in the quality of the resulting datasets.1<\/jats:p>","DOI":"10.1162\/tacl_a_00734","type":"journal-article","created":{"date-parts":[[2025,3,3]],"date-time":"2025-03-03T15:46:41Z","timestamp":1741016801000},"page":"167-187","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":2,"title":["A Confidence-based Acquisition Model for Self-supervised Active\n                    Learning and Label Correction"],"prefix":"10.1162","volume":"13","author":[{"given":"Carel van","family":"Niekerk","sequence":"first","affiliation":[{"name":"Heinrich Heine Universit\u00e4t D\u00fcsseldorf, D\u00fcsseldorf, Germany. cvanniekerk@hhu.de"}]},{"given":"Christian","family":"Geishauser","sequence":"additional","affiliation":[{"name":"Heinrich Heine Universit\u00e4t D\u00fcsseldorf, D\u00fcsseldorf, Germany. geishaus@hhu.de"}]},{"given":"Michael","family":"Heck","sequence":"additional","affiliation":[{"name":"Heinrich Heine Universit\u00e4t D\u00fcsseldorf, D\u00fcsseldorf, Germany. heckmi@hhu.de"}]},{"given":"Shutong","family":"Feng","sequence":"additional","affiliation":[{"name":"Heinrich Heine Universit\u00e4t D\u00fcsseldorf, D\u00fcsseldorf, Germany. fengs@hhu.de"}]},{"given":"Hsien-chin","family":"Lin","sequence":"additional","affiliation":[{"name":"Heinrich Heine Universit\u00e4t D\u00fcsseldorf, D\u00fcsseldorf, Germany. linh@hhu.de"}]},{"given":"Nurul","family":"Lubis","sequence":"additional","affiliation":[{"name":"Heinrich Heine Universit\u00e4t D\u00fcsseldorf, D\u00fcsseldorf, Germany. lubis@hhu.de"}]},{"given":"Benjamin","family":"Ruppik","sequence":"additional","affiliation":[{"name":"Heinrich Heine Universit\u00e4t D\u00fcsseldorf, D\u00fcsseldorf, Germany. ruppik@hhu.de"}]},{"given":"Renato","family":"Vukovic","sequence":"additional","affiliation":[{"name":"Heinrich Heine Universit\u00e4t D\u00fcsseldorf, D\u00fcsseldorf, Germany. revuk100@hhu.de"}]},{"given":"Milica","family":"Ga\u0161i\u0107","sequence":"additional","affiliation":[{"name":"Heinrich Heine Universit\u00e4t D\u00fcsseldorf, D\u00fcsseldorf, Germany. gasic@hhu.de"}]}],"member":"281","published-online":{"date-parts":[[2025,2,28]]},"reference":[{"issue":"3","key":"2025051914251019300_bib1","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1162\/neco.1996.8.3.643","article-title":"The effects of adding noise during backpropagation training\n                        on a generalization performance","volume":"8","author":"An","year":"1996","journal-title":"Neural\n                        Computation"},{"key":"2025051914251019300_bib2","article-title":"Pitfalls of in-domain uncertainty\n                        estimation and ensembling in deep learning","volume-title":"Proceedings of the International Conference on Learning\n                        Representations (ICLR)","author":"Ashukha","year":"2020"},{"key":"2025051914251019300_bib3","article-title":"METEOR: An automatic metric for MT evaluation\n                        with improved correlation with human judgments","volume-title":"Proceedings of the ACL Workshop on Intrinsic and Extrinsic\n                        Evaluation Measures for Machine Translation and\/or Summarization","author":"Banerjee","year":"2005"},{"key":"2025051914251019300_bib4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00976","article-title":"The power of ensembles for active learning\n                        in image classification","volume-title":"2018 IEEE\/CVF Conference\n                        on Computer Vision and Pattern Recognition (CVPR)","author":"Beluch","year":"2018"},{"key":"2025051914251019300_bib5","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W17-4717","article-title":"Findings of the 2017 Conference on Machine\n                        Translation (WMT17)","volume-title":"Proceedings of the Second\n                        Conference on Machine Translation","author":"Bojar","year":"2017"},{"key":"2025051914251019300_bib6","doi-asserted-by":"publisher","first-page":"5016","DOI":"10.18653\/v1\/D18-1547","article-title":"MultiWOZ - 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