@inproceedings{ince-aryal-2025-howard,
    title = "{H}oward {U}niversity-{AI}4{PC} at {S}em{E}val-2025 Task 11: Combining Expert Personas via Prompting for Enhanced Multilingual Emotion Analysis",
    author = "Ince, Amir  and
      Aryal, Saurav",
    editor = "Rosenthal, Sara  and
      Ros{\'a}, Aiala  and
      Ghosh, Debanjan  and
      Zampieri, Marcos",
    booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/transition-to-people-yaml/2025.semeval-1.216/",
    pages = "1645--1655",
    ISBN = "979-8-89176-273-2",
    abstract = "For our approach to SemEval-2025 Task 11, we employ a multi-tier evaluation framework for perceived emotion analysis. Our system consists of a smaller-parameter-size large language model that independently predicts a given text{'}s perceived emotion while explaining the reasoning behind its decision. The initial model{'}s persona is varied through careful prompting, allowing it to represent multiple perspectives. These outputs, including both predictions and reasoning, are aggregated and fed into a final decision-making model that determines the ultimate emotion classification. We evaluated our approach in official SemEval Task 11 on subtasks A and C in all the languages provided."
}