@inproceedings{pan-etal-2023-umuteam,
title = "{UMUT}eam at {S}em{E}val-2023 Task 10: Fine-grained detection of sexism in {E}nglish",
author = "Pan, Ronghao and
Garc{\'\i}a-D{\'\i}az, Jos{\'e} Antonio and
Jim{\'e}nez Zafra, Salud Mar{\'\i}a and
Valencia-Garc{\'\i}a, Rafael",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Da San Martino, Giovanni and
Tayyar Madabushi, Harish and
Kumar, Ritesh and
Sartori, Elisa},
booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.semeval-1.80",
doi = "10.18653/v1/2023.semeval-1.80",
pages = "589--594",
abstract = "In this manuscript, we describe the participation of UMUTeam in the Explainable Detection of Online Sexism shared task proposed at SemEval 2023. This task concerns the precise and explainable detection of sexist content on Gab and Reddit, i.e., developing detailed classifiers that not only identify what is sexist, but also explain why it is sexism. Our participation in the three EDOS subtasks is based on extending new unlabeled sexism data in the Masked Language Model task of a pre-trained model, such as RoBERTa-large to improve its generalization capacity and its performance on classification tasks. Once the model has been pre-trained with the new data, fine-tuning of this model is performed for different specific sexism classification tasks. Our system has achieved excellent results in this competitive task, reaching top 24 (84) in Task A, top 23 (69) in Task B, and top 13 (63) in Task C.",
}
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<abstract>In this manuscript, we describe the participation of UMUTeam in the Explainable Detection of Online Sexism shared task proposed at SemEval 2023. This task concerns the precise and explainable detection of sexist content on Gab and Reddit, i.e., developing detailed classifiers that not only identify what is sexist, but also explain why it is sexism. Our participation in the three EDOS subtasks is based on extending new unlabeled sexism data in the Masked Language Model task of a pre-trained model, such as RoBERTa-large to improve its generalization capacity and its performance on classification tasks. Once the model has been pre-trained with the new data, fine-tuning of this model is performed for different specific sexism classification tasks. Our system has achieved excellent results in this competitive task, reaching top 24 (84) in Task A, top 23 (69) in Task B, and top 13 (63) in Task C.</abstract>
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%0 Conference Proceedings
%T UMUTeam at SemEval-2023 Task 10: Fine-grained detection of sexism in English
%A Pan, Ronghao
%A García-Díaz, José Antonio
%A Jiménez Zafra, Salud María
%A Valencia-García, Rafael
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F pan-etal-2023-umuteam
%X In this manuscript, we describe the participation of UMUTeam in the Explainable Detection of Online Sexism shared task proposed at SemEval 2023. This task concerns the precise and explainable detection of sexist content on Gab and Reddit, i.e., developing detailed classifiers that not only identify what is sexist, but also explain why it is sexism. Our participation in the three EDOS subtasks is based on extending new unlabeled sexism data in the Masked Language Model task of a pre-trained model, such as RoBERTa-large to improve its generalization capacity and its performance on classification tasks. Once the model has been pre-trained with the new data, fine-tuning of this model is performed for different specific sexism classification tasks. Our system has achieved excellent results in this competitive task, reaching top 24 (84) in Task A, top 23 (69) in Task B, and top 13 (63) in Task C.
%R 10.18653/v1/2023.semeval-1.80
%U https://aclanthology.org/2023.semeval-1.80
%U https://doi.org/10.18653/v1/2023.semeval-1.80
%P 589-594
Markdown (Informal)
[UMUTeam at SemEval-2023 Task 10: Fine-grained detection of sexism in English](https://aclanthology.org/2023.semeval-1.80) (Pan et al., SemEval 2023)
ACL