@inproceedings{ebrahimi-etal-2024-sharif-str,
    title = "Sharif-{STR} at {S}em{E}val-2024 Task 1: Transformer as a Regression Model for Fine-Grained Scoring of Textual Semantic Relations",
    author = "Ebrahimi, Seyedeh Fatemeh  and
      Akhavan Azari, Karim  and
      Iravani, Amirmasoud  and
      Alizadeh, Hadi  and
      Taghavi, Zeinab  and
      Sameti, Hossein",
    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/jlcl-multiple-ingestion/2024.semeval-1.151/",
    doi = "10.18653/v1/2024.semeval-1.151",
    pages = "1043--1052",
    abstract = "This paper explores semantic textual relatedness (STR) using fine-tuning techniques on the RoBERTa transformer model, focusing on sentence-level STR within Track A (Supervised). The study evaluates the effectiveness of this approach across different languages, with promising results in English and Spanish but encountering challenges in Arabic."
}