@inproceedings{9e3a4b3e38d34a21ade2555b37353e19,
title = "HITMI\&T at SemEval-2021 Task 5: Integrating Transformer and CRF for Toxic Spans Detection",
abstract = "This paper introduces our system at SemEval-2021 Task 5: Toxic Spans Detection. The task aims to accurately locate toxic spans within a text. Using BIO tagging scheme, we model the task as a token-level sequence labeling task. Our system uses a single model built on the model of multi-layer bidirectional transformer encoder. And we introduce conditional random field (CRF) to make the model learn the constraints between tags. We use ERNIE as pre-trained model, which is more suitable for the task accroding to our experiments. In addition, we use adversarial training with the fast gradient method (FGM) to improve the robustness of the system. Our system obtains 69.85\% F1 score, ranking 3rd for the official evaluation.",
author = "Chenyi Wang and Tianshu Liu and Tiejun Zhao",
note = "Publisher Copyright: {\textcopyright} 2021 Association for Computational Linguistics.; 15th International Workshop on Semantic Evaluation, SemEval 2021, co-located with The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL-IJCNLP 2021 ; Conference date: 05-08-2021 Through 06-08-2021",
year = "2021",
doi = "10.18653/v1/2021.semeval-1.117",
language = "英语",
series = "SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "870--874",
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",
address = "澳大利亚",
}