LCT-1 at SemEval-2023 Task 10: Pre-training and Multi-task Learning for Sexism Detection and Classification

Konstantin Chernyshev*, Ekaterina Garanina*, Duygu Bayram, Qiankun Zheng, Lukas Edman

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

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Samenvatting

Misogyny and sexism are growing problems in social media. Advances have been made in online sexism detection but the systems are often uninterpretable. SemEval-2023 Task 10 on Explainable Detection of Online Sexism aims at increasing explainability of the sexism detection, and our team participated in all the proposed subtasks. Our system is based on further domain-adaptive pre-training (Gururangan et al., 2020). Building on the Transformer-based models with the domain adaptation, we compare fine-tuning with multi-task learning and show that each subtask requires a different system configuration.

Originele taal-2English
Titel17th International Workshop on Semantic Evaluation, SemEval 2023 - Proceedings of the Workshop
RedacteurenAtul Kr. Ojha, A. Seza Dogruoz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
UitgeverijAssociation for Computational Linguistics, ACL Anthology
Pagina's1573-1581
Aantal pagina's9
ISBN van elektronische versie9781959429999
DOI's
StatusPublished - 2023
Evenement17th International Workshop on Semantic Evaluation, SemEval 2023, co-located with the 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023 - Hybrid, Toronto, Canada
Duur: 13-jul.-202314-jul.-2023

Conference

Conference17th International Workshop on Semantic Evaluation, SemEval 2023, co-located with the 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023
Land/RegioCanada
StadHybrid, Toronto
Periode13/07/202314/07/2023

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