@inproceedings{feldman-peng-2026-lexical,
    title = "Lexical Availability and Human Distributional Agreement in {GPT}-4o{'}s Color Naming",
    author = "Feldman, Anna  and
      Peng, Jing",
    editor = "Mohammad, Saif M.  and
      Ousidhoum, Nedjma",
    booktitle = "Proceedings of the 15th Joint Conference on Lexical and Computational Semantics (*{SEM} 2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.starsem-conference.9/",
    pages = "136--147",
    ISBN = "979-8-89176-413-2",
    abstract = "We evaluate GPT-4o{'}s color naming across nine languages using both synthetic and human-derived stimuli. Using hue wheels, fixed basic categories, low-chroma hue lines, and dense binned CIELAB grids, we separate lexical availability of color terms from distributional agreement with human color naming. GPT-4o reliably names vivid, high-chroma colors and reproduces several known language-specific distinctions under constrained settings. However, its performance degrades sharply for low-chroma colors and for stimuli near human category boundaries. In these regions, model-human divergence remains high. Overall, GPT-4o shows strong cross-linguistic lexical knowledge but does not reliably match human color-naming distributions, especially in low-chroma and boundary regions."
}