@inproceedings{rostamkhani-etal-2023-rozam,
    title = "{ROZAM} at {S}em{E}val 2023 Task 9: Multilingual Tweet Intimacy Analysis",
    author = "Rostamkhani, Mohammadmostafa  and
      Zamaninejad, Ghazal  and
      Eetemadi, Sauleh",
    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-1.278",
    doi = "10.18653/v1/2023.semeval-1.278",
    pages = "2029--2032",
    abstract = "We build a model using large multilingual pretrained language model XLM-T for regression task and fine-tune it on the MINT (Multilingual INTmacy) analysis dataset which covers 6 languages for training and 4 languages for testing zero-shot performance of the model. The dataset was annotated and the annotations are intimacy scores. We experiment with several deep learning architectures to predict intimacy score. To achieve optimal performance we modify several model settings including loss function, number and type of layers. In total, we ran 16 end-to-end experiments. Our best system achieved a Pearson Correlation score of 0.52.",
}

We build a model using large multilingual pretrained language model XLM-T for regression task and fine-tune it on the MINT (Multilingual INTmacy) analysis dataset which covers 6 languages for training and 4 languages for testing zero-shot performance of the model. The dataset was annotated and the annotations are intimacy scores. We experiment with several deep learning architectures to predict intimacy score. To achieve optimal performance we modify several model settings including loss function, number and type of layers. In total, we ran 16 end-to-end experiments. Our best system achieved a Pearson Correlation score of 0.52.
Rostamkhani, Mohammadmostafa Zamaninejad, Ghazal Eetemadi, Sauleh
ROZAM at SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis