@inproceedings{baswani-etal-2023-ltrc,
    title = "{LTRC} at {S}em{E}val-2023 Task 6: Experiments with Ensemble Embeddings",
    author = "Baswani, Pavan  and
      Sri Adibhatla, Hiranmai  and
      Shrivastava, Manish",
    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-1.116",
    doi = "10.18653/v1/2023.semeval-1.116",
    pages = "841--846",
    abstract = "In this paper, we present our team{'}s involvement in Task 6: LegalEval: Understanding Legal Texts. The task comprised three subtasks, and we focus on subtask A: Rhetorical Roles prediction. Our approach included experimenting with pre-trained embeddings and refining them with statistical and neural classifiers. We provide a thorough examination ofour experiments, solutions, and analysis, culminating in our best-performing model and current progress. We achieved a micro F1 score of 0.6133 on the test data using fine-tuned LegalBERT embeddings.",
}

In this paper, we present our team{'}s involvement in Task 6: LegalEval: Understanding Legal Texts. The task comprised three subtasks, and we focus on subtask A: Rhetorical Roles prediction. Our approach included experimenting with pre-trained embeddings and refining them with statistical and neural classifiers. We provide a thorough examination ofour experiments, solutions, and analysis, culminating in our best-performing model and current progress. We achieved a micro F1 score of 0.6133 on the test data using fine-tuned LegalBERT embeddings.
Baswani, Pavan Sri Adibhatla, Hiranmai Shrivastava, Manish
LTRC at SemEval-2023 Task 6: Experiments with Ensemble Embeddings