@inproceedings{38dbd53644fe41749d1901b5712a2fb6,
title = "Integrating Plutchik's Theory with Mixture of Experts for Enhancing Emotion Classification",
abstract = "Emotion significantly influences human behavior and decision-making processes. We propose a labeling methodology grounded in Plutchik's Wheel of Emotions theory for emotion classification. Furthermore, we employ a Mixture of Experts (MoE) architecture to evaluate the efficacy of this labeling approach, by identifying the specific emotions that each expert learns to classify. Experimental results reveal that our methodology improves the performance of emotion classification.",
author = "Dongjun Lim and Cheong, \{Yun Gyung\}",
note = "Publisher Copyright: {\textcopyright} 2024 Association for Computational Linguistics.; 2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024 ; Conference date: 12-11-2024 Through 16-11-2024",
year = "2024",
doi = "10.18653/v1/2024.emnlp-main.50",
language = "English",
series = "EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "857--867",
editor = "Yaser Al-Onaizan and Mohit Bansal and Yun-Nung Chen",
booktitle = "EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference",
}