@inproceedings{motegi-etal-2026-identifying,
    title = "Identifying Implicit Research Data References in Paper Citations",
    author = "Motegi, Koshi  and
      Ito, Koichiro  and
      Matsubara, Shigeki",
    editor = "Rehm, Georg  and
      Dietze, Stefan  and
      Dessi, Danilo  and
      Maynard, Diana  and
      Schimmler, Sonja",
    booktitle = "Proceedings of Natural Scientific Language Processing ({NSLP}) @ {LREC} 2026",
    month = may,
    year = "2026",
    address = "Palma, Mallorca (Spain)",
    publisher = "ELRA Language Resources Association (ELRA)",
    url = "https://preview.aclanthology.org/revision-workflow/2026.nslp-1.18/",
    doi = "10.63317/2g9fq97f2h2j",
    pages = "186--192",
    abstract = "To encourage the public release of research data under open science, it is beneficial to establish mechanisms for evaluating research data based on metrics such as citation counts. In scholarly papers, authors sometimes cite papers that report the creation or release of research data instead of citing the research data themselves. In this paper, as a step toward computing citation counts of research data, we investigate the feasibility of identifying paper citations that refer to research data. We conducted an identification experiment using large language models and evaluated their performance."
}