@inproceedings{ding-etal-2023-catalpa,
    title = "{CATALPA}{\_}{E}du{NLP} at {P}rag{T}ag-2023",
    author = "Ding, Yuning  and
      Bexte, Marie  and
      Horbach, Andrea",
    editor = "Alshomary, Milad  and
      Chen, Chung-Chi  and
      Muresan, Smaranda  and
      Park, Joonsuk  and
      Romberg, Julia",
    booktitle = "Proceedings of the 10th Workshop on Argument Mining",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2023.argmining-1.22/",
    doi = "10.18653/v1/2023.argmining-1.22",
    pages = "197--201",
    abstract = "This paper describes our contribution to the PragTag-2023 Shared Task. We describe and compare different approaches based on sentence classification, sentence similarity, and sequence tagging. We find that a BERT-based sentence labeling approach integrating positional information outperforms both sequence tagging and SBERT-based sentence classification. We further provide analyses highlighting the potential of combining different approaches."
}