@inproceedings{duran-silva-accuosto-2025-dynamic,
    title = "Dynamic Reference Extraction and Linking across Multiple Scholarly Knowledge Graphs",
    author = "Duran-Silva, Nicolau  and
      Accuosto, Pablo",
    editor = "Accomazzi, Alberto  and
      Ghosal, Tirthankar  and
      Grezes, Felix  and
      Lockhart, Kelly",
    booktitle = "Proceedings of the Third Workshop for Artificial Intelligence for Scientific Publications",
    month = dec,
    year = "2025",
    address = "Mumbai, India and virtual",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.wasp-main.9/",
    pages = "80--86",
    ISBN = "979-8-89176-310-4",
    abstract = "References are an important feature of scientific literature; however, they are unstructured, heterogeneous, noisy, and often multilingual. We present a modular pipeline that leverages fine-tuned transformer models for reference location, classification, parsing, retrieval, and re-ranking across multiple scholarly knowledge graphs, with a focus on multilingual and non-traditional sources such as patents and policy documents. Our main contributions are: a unified pipeline for reference extraction and linking across diverse document types, openly released annotated datasets, fine-tuned models for each subtask, and evaluations across multiple scholarly knowledge graphs, enabling richer, more inclusive infrastructures for open research information."
}