@inproceedings{19fedf46600d4a9588f83c8f63e6c9cb,
title = "The University of Arizona at SemEval-2021 Task 10: Applying Self-training, Active Learning and Data Augmentation to Source-free Domain Adaptation",
abstract = "This paper describes our systems for negation detection and time expression recognition in SemEval 2021 Task 10, Source-Free Domain Adaptation for Semantic Processing. We show that self-training, active learning and data augmentation techniques can improve the generalization ability of the model on the unlabeled target domain data without accessing source domain data. We also perform detailed ablation studies and error analyses for our time expression recognition systems to identify the source of the performance improvement and give constructive feedback on the temporal normalization annotation guidelines.",
author = "Xin Su and Yiyun Zhao and Steven Bethard",
note = "Publisher Copyright: {\textcopyright} 2021 Association for Computational Linguistics.; 15th International Workshop on Semantic Evaluation, SemEval 2021 ; Conference date: 05-08-2021 Through 06-08-2021",
year = "2021",
doi = "10.18653/v1/2021.semeval-1.56",
language = "English (US)",
series = "SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "458--466",
editor = "Alexis Palmer and Nathan Schneider and Natalie Schluter and Guy Emerson and Aurelie Herbelot and Xiaodan Zhu",
booktitle = "SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop",
}