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Multilingual toxic comment classifier using XLM-RoBERTa achieving ROC-AUC of 0.9922, detecting toxic content across Hindi and English text for scalable cross-lingual content moderation.
Fake news detector using RoBERTa achieving 99.87% accuracy by analyzing news titles and article content to automatically identify misleading information at scale.
Real-time disaster tweet classifier using BERTweet achieving Macro F1-Score of =0.8955 to help first responders identify critical information from social media during emergencies.
