@inproceedings{rizzi-etal-2023-mind,
    title = "{MIND} at {S}em{E}val-2023 Task 11: From Uncertain Predictions to Subjective Disagreement",
    author = "Rizzi, Giulia  and
      Astorino, Alessandro  and
      Scalena, Daniel  and
      Rosso, Paolo  and
      Fersini, Elisabetta",
    editor = {Ojha, Atul Kr.  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Da San Martino, Giovanni  and
      Tayyar Madabushi, Harish  and
      Kumar, Ritesh  and
      Sartori, Elisa},
    booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.semeval-1.77",
    doi = "10.18653/v1/2023.semeval-1.77",
    pages = "556--564",
    abstract = "This paper describes the participation of the research laboratory MIND, at the University of Milano-Bicocca, in the SemEval 2023 task related to Learning With Disagreements (Le-Wi-Di). The main goal is to identify the level of agreement/disagreement from a collection of textual datasets with different characteristics in terms of style, language and task. The proposed approach is grounded on the hypothesis that the disagreement between annotators could be grasped by the uncertainty that a model, based on several linguistic characteristics, could have on the prediction of a given gold label.",
}

This paper describes the participation of the research laboratory MIND, at the University of Milano-Bicocca, in the SemEval 2023 task related to Learning With Disagreements (Le-Wi-Di). The main goal is to identify the level of agreement/disagreement from a collection of textual datasets with different characteristics in terms of style, language and task. The proposed approach is grounded on the hypothesis that the disagreement between annotators could be grasped by the uncertainty that a model, based on several linguistic characteristics, could have on the prediction of a given gold label.
Rizzi, Giulia Astorino, Aless ro Scalena, Daniel Rosso, Paolo Fersini, Elisabetta
MIND at SemEval-2023 Task 11: From Uncertain Predictions to Subjective Disagreement