GiusBERTo: A Legal Language Model for Personal Data De-identification in Italian Court of Auditors Decisions
<|reference_start|>GiusBERTo: A Legal Language Model for Personal Data De-identification in Italian Court of Auditors Decisions: Recent advances in Natural Language Processing have demonstrated the effectiveness of pretrained language models like BERT for a variety of downstream tasks. We present GiusBERTo, the first BERT-based model specialized for anonymizing personal data in Italian legal documents. GiusBERTo is trained on a large dataset of Court of Auditors decisions to recognize entities to anonymize, including names, dates, locations, while retaining contextual relevance. We evaluate GiusBERTo on a held-out test set and achieve 97% token-level accuracy. GiusBERTo provides the Italian legal community with an accurate and tailored BERT model for de-identification, balancing privacy and data protection.<|reference_end|>
@article{salierno2024giusberto:,
    title={GiusBERTo: A Legal Language Model for Personal Data De-identification in
  Italian Court of Auditors Decisions},
    author={Giulio Salierno, Rosamaria Bert`e, Luca Attias, Carla Morrone, Dario
  Pettazzoni, Daniela Battisti},
    journal={arXiv preprint arXiv:2406.15032},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.15032},
    primaryClass={cs.CL cs.AI}
}