Adversarial Evaluation of Large Language Models for Building Robust Offensive Language Detection in Moroccan Arabic

Offensive language detection is crucial for ensuring safe and inclusive digital environments. Identifying harmful content protects users and supports healthier online interactions. Despite advances in transformer-based models, particularly Large Language Models (LLMs), their application to this task...

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Detalhes bibliográficos

Principais autores:	Soufiyan Ouali, Kanza Raisi, Asmaa Mourhir, El Habib Nfaoui, Said El Garouani
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2026-04-01
coleção:	Big Data and Cognitive Computing
Assuntos:	robust AI for low-resource language Moroccan Arabic Arabic dialects LLMs for low-resource language offensive speech recognition adversarial training
Acesso em linha:	https://www.mdpi.com/2504-2289/10/5/132
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