@inproceedings{zelch-etal-2025-reproducing,
    title = "Reproducing the Argument Quality Prediction of Project Debater",
    author = "Zelch, Ines  and
      Hagen, Matthias  and
      Stein, Benno  and
      Kiesel, Johannes",
    editor = "Chistova, Elena  and
      Cimiano, Philipp  and
      Haddadan, Shohreh  and
      Lapesa, Gabriella  and
      Ruiz-Dolz, Ramon",
    booktitle = "Proceedings of the 12th Argument mining Workshop",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/display_plenaries/2025.argmining-1.17/",
    pages = "181--188",
    ISBN = "979-8-89176-258-9",
    abstract = "A crucial task when analyzing arguments is to determine their quality. Especially when you have to choose from a large number of suitable arguments, the determination of a reliable argument quality value is of great benefit. Probably the best-known model for determining such an argument quality value was developed in IBM{'}s Project Debater and made available to the research community free of charge via an API. In fact, the model was never open and the API is no longer available. In this paper, IBM{'}s model is reproduced using the freely available training data and the description in the corresponding publication. Our reproduction achieves similar results on the test data as described in the original publication. Further, the predicted quality scores of reproduction and original show a very high correlation (Pearson{'}s $r=0.9$) on external data."
}