@inproceedings{noce-etal-2026-jurifindit,
    title = "{J}uri{F}ind{IT}: an {I}talian legal retrieval dataset",
    author = "Noce, Niko Dalla  and
      Colla, Davide  and
      Doust, Sina Farhang  and
      De Mattei, Lorenzo  and
      Bacciu, Davide",
    editor = "Demberg, Vera  and
      Inui, Kentaro  and
      Marquez, Llu{\'i}s",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {EACL} 2026",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.findings-eacl.221/",
    pages = "4223--4241",
    ISBN = "979-8-89176-386-9",
    abstract = "Statutory article retrieval (SAR) targets retrieval of legislative provisions relevant to a natural language question. The lexical gap between everyday queries and specialized legal language, as well as the structural dependencies of statute law, makes it a challenging task. Here, we introduce JuriFindIT, the first SAR dataset for the Italian legal domain and the first to explicitly encode cross-article references extracted from national legal code. The dataset covers four macro-areas{---}civil law, criminal law, anti-money laundering and counter-terrorism, and privacy{---}and includes 895 expert-authored questions and 169,301 generated ones, linked to more than 23,000 statutory articles. We provide retrieval models fine-tuned on JuriFindIT, proposing a pipeline that integrates dense encoders with an heterogeneous legislative graph, achieving consistent improvements over prior SAR approaches."
}