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This document discusses a study aimed at developing an automated system for detecting abusive language directed at women in Tamil and Malayalam on social media platforms. Utilizing multilingual BERT (mBERT) and XLM-R models, the research achieved F1 scores of 0.75 for Tamil and 0.68 for Malayalam, highlighting the challenges of detecting nuanced abusive language in low-resource languages. The study emphasizes the need for improved contextual understanding and larger annotated datasets to enhance detection a

Author

jnana saisree

Language

EN