@inproceedings{chen-etal-2020-ntu,
title = "{NTU}{\_}{NLP} at {S}em{E}val-2020 Task 12: Identifying Offensive Tweets Using Hierarchical Multi-Task Learning Approach",
author = "Chen, Po-Chun and
Huang, Hen-Hsen and
Chen, Hsin-Hsi",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.279/",
doi = "10.18653/v1/2020.semeval-1.279",
pages = "2105--2110",
abstract = "This paper presents our hierarchical multi-task learning (HMTL) and multi-task learning (MTL) approaches for improving the text encoder in Sub-tasks A, B, and C of Multilingual Offensive Language Identification in Social Media (SemEval-2020 Task 12). We show that using the MTL approach can greatly improve the performance of complex problems, i.e. Sub-tasks B and C. Coupled with a hierarchical approach, the performances are further improved. Overall, our best model, HMTL outperforms the baseline model by 3{\%} and 2{\%} of Macro F-score in Sub-tasks B and C of OffensEval 2020, respectively."
}
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%0 Conference Proceedings
%T NTU_NLP at SemEval-2020 Task 12: Identifying Offensive Tweets Using Hierarchical Multi-Task Learning Approach
%A Chen, Po-Chun
%A Huang, Hen-Hsen
%A Chen, Hsin-Hsi
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F chen-etal-2020-ntu
%X This paper presents our hierarchical multi-task learning (HMTL) and multi-task learning (MTL) approaches for improving the text encoder in Sub-tasks A, B, and C of Multilingual Offensive Language Identification in Social Media (SemEval-2020 Task 12). We show that using the MTL approach can greatly improve the performance of complex problems, i.e. Sub-tasks B and C. Coupled with a hierarchical approach, the performances are further improved. Overall, our best model, HMTL outperforms the baseline model by 3% and 2% of Macro F-score in Sub-tasks B and C of OffensEval 2020, respectively.
%R 10.18653/v1/2020.semeval-1.279
%U https://aclanthology.org/2020.semeval-1.279/
%U https://doi.org/10.18653/v1/2020.semeval-1.279
%P 2105-2110
Markdown (Informal)
[NTU_NLP at SemEval-2020 Task 12: Identifying Offensive Tweets Using Hierarchical Multi-Task Learning Approach](https://aclanthology.org/2020.semeval-1.279/) (Chen et al., SemEval 2020)
ACL