@inproceedings{jiang-etal-2024-blm,
    title = "{BLM}-It - Blackbird Language Matrices for {I}talian: A {CALAMITA} Challenge",
    author = "Jiang, Chunyang  and
      Samo, Giuseppe  and
      Nastase, Vivi  and
      Merlo, Paola",
    editor = "Dell'Orletta, Felice  and
      Lenci, Alessandro  and
      Montemagni, Simonetta  and
      Sprugnoli, Rachele",
    booktitle = "Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)",
    month = dec,
    year = "2024",
    address = "Pisa, Italy",
    publisher = "CEUR Workshop Proceedings",
    url = "https://preview.aclanthology.org/ingest_wac_2008/2024.clicit-1.125/",
    pages = "1135--1143",
    ISBN = "979-12-210-7060-6",
    abstract = "In this challenge, we propose Blackbird Language Matrices (BLMs), linguistic puzzles to learn language-related problems and delve into deeper formal and semantic properties of language, through a process of paradigm understanding. A BLM matrix consists of a context set and an answer set. The context is a sequence of sentences that encode implicitly an underlying generative linguistic rule. The contrastive multiple-choice answer set includes negative examples following corrupted generating rules. We propose three subtasks {---}agreement concord, causative and object-drop alternation detection{---} each in two variants of increasing lexical complexity.The datasets comprise a few prompts for few-shot learning and a large test set."
}