Multi-task detection of harmful content in code-mixed meme captions using large language models with zero-shot, few-shot, and fine-tuning approaches

In today’s digital world, memes have become a common form of communication, shaping online conversations and reflecting social events. However, some memes can negatively impact people’s emotions, especially when they involve sensitive topics or mock certain groups or individuals. To address this iss...

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Autors principals:	A.K. Indira Kumar, Gayathri Sthanusubramoniani, Deepa Gupta, Aarathi Rajagopalan Nair, Yousef Ajami Alotaibi, Mohammed Zakariah
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2025-06-01
Col·lecció:	Egyptian Informatics Journal
Matèries:	Text classification Code-mixed data Large language models Cyberbully detection Sarcasm detection Sentimental analysis
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S1110866525000763
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