Geetanjali Kale


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2024

pdf bib
PICT at StanceEval2024: Stance Detection in Arabic using Ensemble of Large Language Models
Ishaan Shukla | Ankit Vaidya | Geetanjali Kale
Proceedings of the Second Arabic Natural Language Processing Conference

This paper outlines our approach to the StanceEval 2024- Arabic Stance Evaluation shared task. The goal of the task was to identify the stance, one out of three (Favor, Against or None) towards tweets based on three topics, namely- COVID-19 Vaccine, Digital Transformation and Women Empowerment. Our approach consists of fine-tuning BERT-based models efficiently for both, Single-Task Learning as well as Multi-Task Learning, the details of which are discussed. Finally, an ensemble was implemented on the best-performing models to maximize overall performance. We achieved a macro F1 score of 78.02% in this shared task. Our codebase is available publicly.