@inproceedings{bruera-etal-2022-generating,
    title = "Generating Realistic Synthetic Curricula Vitae for Machine Learning Applications under Differential Privacy",
    author = "Bruera, Andrea  and
      Alda, Francesco  and
      Di Cerbo, Francesco",
    editor = "Siegert, Ingo  and
      Rigault, Mickael  and
      Arranz, Victoria",
    booktitle = "Proceedings of the Workshop on Ethical and Legal Issues in Human Language Technologies and Multilingual De-Identification of Sensitive Data In Language Resources within the 13th Language Resources and Evaluation Conference",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.legal-1.11/",
    pages = "53--63",
    abstract = "Applications involving machine learning in Human Resources (HR, the management of human talent in order to accomplish organizational goals) must respect the privacy of the individuals whose data is being used. This is a difficult aim, given the extremely personal nature of text data handled by HR departments, such as Curricula Vitae (CVs)."
}