Abstract
We present our submission to SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS). We address all three tasks: Task A consists of identifying whether a post is sexist. If so, Task B attempts to assign it one of four categories: threats, derogation, animosity, and prejudiced discussions. Task C aims for an even more fine-grained classification, divided among 11 classes. Our team UniBoe’s experiments with fine-tuning of hate-tuned Transformer-based models and priming for generative models. In addition, we explore model-agnostic strategies, such as data augmentation techniques combined with active learning, as well as obfuscation of identity terms. Our official submissions obtain an F1_score of 0.83 for Task A, 0.58 for Task B and 0.32 for Task C.- Anthology ID:
- 2023.semeval-1.158
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1138–1147
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.158
- DOI:
- 10.18653/v1/2023.semeval-1.158
- Cite (ACL):
- Arianna Muti, Francesco Fernicola, and Alberto Barrón-Cedeño. 2023. UniBoe’s at SemEval-2023 Task 10: Model-Agnostic Strategies for the Improvement of Hate-Tuned and Generative Models in the Classification of Sexist Posts. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1138–1147, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- UniBoe’s at SemEval-2023 Task 10: Model-Agnostic Strategies for the Improvement of Hate-Tuned and Generative Models in the Classification of Sexist Posts (Muti et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2023.semeval-1.158.pdf