@inproceedings{siino-2024-transmistral,
    title = "{T}rans{M}istral at {S}em{E}val-2024 Task 10: Using Mistral 7{B} for Emotion Discovery and Reasoning its Flip in Conversation",
    author = "Siino, Marco",
    editor = {Ojha, Atul Kr.  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Tayyar Madabushi, Harish  and
      Da San Martino, Giovanni  and
      Rosenthal, Sara  and
      Ros{\'a}, Aiala},
    booktitle = "Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)",
    month = jun,
    year = "2024",
    address = "Mexico City, Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.semeval-1.46/",
    doi = "10.18653/v1/2024.semeval-1.46",
    pages = "298--304",
    abstract = "The EDiReF shared task at SemEval 2024 comprises three subtasks: Emotion Recognition in Conversation (ERC) in Hindi-English code-mixed conversations, Emotion Flip Reasoning (EFR) in Hindi-English code-mixed conversations, and EFR in English conversations. The objectives for the ERC and EFR tasks are defined as follows: 1) Emotion Recognition in Conversation (ERC): In this task, participants are tasked with assigning an emotion to each utterance within a dialogue from a predefined set of possible emotions. The goal is to accurately recognize and label the emotions expressed in the conversation; 2) Emotion Flip Reasoning (EFR): This task involves identifying the trigger utterance(s) for an emotion-flip within a multi-party conversation dialogue. Participants are required to pinpoint the specific utterance(s) that serve as catalysts for a change in emotion during the conversation. In this paper we only address the first subtask (ERC) making use of an online translation strategy followed by the application of a Mistral 7B model together with a few-shot prompt strategy. Our approach obtains an F1 of 0.36, eventually exhibiting further room for improvements."
}