@inproceedings{kumar-etal-2023-oda,
    title = "{ODA}{\_}{SRIB} at {S}em{E}val-2023 Task 9: A Multimodal Approach for Improved Intimacy Analysis",
    author = "Kumar, Priyanshu  and
      Kumar, Amit  and
      Prakash, Jiban  and
      Lamba, Prabhat  and
      Abdul, Irfan",
    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-1.233",
    doi = "10.18653/v1/2023.semeval-1.233",
    pages = "1676--1680",
    abstract = "We experiment with XLM-Twitter and XLM-RoBERTa models to predict the intimacy scores in Tweets i.e. the extent to which a Tweet contains intimate content. We propose a Transformer-TabNet based multimodal architecture using text data and statistical features from the text, which performs better than the vanilla Transformer based model. We further experiment with Adversarial Weight Perturbation to make our models generalized and robust. The ensemble of four of our best models achieve an over-all Pearson Coefficient of 0.5893 on the test dataset.",
}

We experiment with XLM-Twitter and XLM-RoBERTa models to predict the intimacy scores in Tweets i.e. the extent to which a Tweet contains intimate content. We propose a Transformer-TabNet based multimodal architecture using text data and statistical features from the text, which performs better than the vanilla Transformer based model. We further experiment with Adversarial Weight Perturbation to make our models generalized and robust. The ensemble of four of our best models achieve an over-all Pearson Coefficient of 0.5893 on the test dataset.
Kumar, Priyanshu Kumar, Amit Prakash, Jiban Lamba, Prabhat Abdul, Irfan
ODA_SRIB at SemEval-2023 Task 9: A Multimodal Approach for Improved Intimacy Analysis