@inproceedings{arrington-etal-2025-conshift,
    title = "{C}on{S}hift: Sense-based Language Variation Analysis using Flexible Alignment",
    author = "Arrington, Clare  and
      Gruppi, Mauricio  and
      Adali, Sibel",
    editor = "Chiruzzo, Luis  and
      Ritter, Alan  and
      Wang, Lu",
    booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.findings-naacl.9/",
    pages = "167--181",
    ISBN = "979-8-89176-195-7",
    abstract = "We introduce ConShift, a family of alignment-based algorithms that enable semantic variation analysis at the sense-level. Using independent senses of words induced from the context of tokens in two corpora, sense-enriched word embeddings are aligned using self-supervision and a flexible matching mechanism. This approach makes it possible to test for multiple sense-level language variations such as sense gain/presence, loss/absence and broadening/narrowing, while providing explanation of the changes through visualization of related concepts. We illustrate the utility of the method with sense- and word-level semantic shift detection results for multiple evaluation datasets in diachronic settings and dialect variation in the synchronic setting."
}