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2025 NAACL NAACL 2025

Overview of the Shared Task on Detecting AI Generated Product Reviews in Dravidian Languages: DravidianLangTech@NAACL 2025

Abstract

AbstractThe detection of AI-generated product reviews is critical due to the increased use of large language models (LLMs) and their capability to generate convincing sentences. The AI-generated reviews can affect the consumers and businesses as they influence the trust and decision-making. This paper presents the overview of the shared task on Detecting AI-generated product reviews in Dravidian Languages” organized as part of DravidianLangTech@NAACL 2025. This task involves two subtasks—one in Malayalam and another in Tamil, both of which are binary classifications where a review is to be classified as human-generated or AI-generated. The dataset was curated by collecting comments from YouTube videos. Various machine learning and deep learning-based models ranging from SVM to transformer-based architectures were employed by the participants.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning and Natural Language Processing
🐝 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

Authors

Premjith B , Nandhini Kumaresh , Bharathi Raja Chakravarthi , Thenmozhi Durairaj , Balasubramanian Palani , Sajeetha Thavareesan , Prasanna Kumar Kumaresan

Topics

Artificial Intelligence > Core AI > Foundation Models Natural Language Processing > Applications > Text Classification Machine Learning > Learning Types > Deep Learning Machine Learning > Learning Types > Classification

Keywords

binary classification text classification ai-generated content deep learning low-resource language product review fake review detection large language model
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