Cross-lingual Emotion Detection through Large Language Models
Ram Mohan Rao Kadiyala · 2024
This paper presents a detailed system description of our entry which finished 1st with a large lead at WASSA 2024 Task 2, focused on crosslingual emotion detection.We utilized a combination of large language models (LLMs) and their ensembles to effectively understand and categorize emotions across different languages.Our approach not only outperformed other submissions with a large margin, but also demonstrated the strength of integrating multiple models to enhance performance.Additionally, We conducted a thorough comparison of the benefits and limitations of each model used.An error analysis is included along with suggested areas for future improvement.This paper aims to offer a clear and comprehensive understanding of advanced techniques in emotion detection, making it accessible even to those new to the field.