2025
NAACL
NAACL 2025
TeamVision@DravidianLangTech 2025: Detecting AI generated product reviews in Dravidian Languages
Abstract
AbstractRecent advancements in natural language processing (NLP) have enabled artificial intelligence (AI) models to generate product reviewsthat are indistinguishable from those written by humans. To address these concerns, this study proposes an effective AI detector model capable of differentiating between AI-generated and human-written product reviews. Our methodology incorporates various machine learning techniques, including Naive Bayes, Random Forest, Logistic Regression, SVM, and deep learning approaches based on the BERT architecture.Our findings reveal that BERT outperforms other models in detecting AI-generated content in both Tamil product reviews and Malayalam product reviews.
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio