@inproceedings{wullschleger-etal-2026-reference,
    title = "Reference-Free Evaluation of Taxonomies",
    author = "Wullschleger, Pascal  and
      Zarharan, Majid  and
      Daly, Donnacha  and
      Pouly, Marc  and
      Foster, Jennifer",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.findings-acl.1273/",
    pages = "25489--25507",
    ISBN = "979-8-89176-395-1",
    abstract = "We introduce two reference-free metrics for quality evaluation of taxonomies in the absence of labels. The first metric evaluates robustness by calculating the correlation between semantic and taxonomic similarity, addressing error types not considered by existing metrics. The second uses Natural Language Inference to assess logical adequacy. Both metrics are tested on five taxonomies and are shown to correlate well with F1 against ground truth taxonomies. We further demonstrate that our metrics can predict downstream performance in hierarchical classification when used with label hierarchies."
}