@inproceedings{hussain-etal-2025-rebuttal,
    title = "A rebuttal of two common deflationary stances against {LLM} cognition",
    author = "Hussain, Zak  and
      Mata, Rui  and
      Wulff, Dirk U.",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/display_plenaries/2025.findings-acl.1242/",
    pages = "24208--24213",
    ISBN = "979-8-89176-256-5",
    abstract = "Large language models (LLMs) are arguably the most predictive models of human cognition available. Despite their impressive human-alignment, LLMs are often labeled as ``*just* next-token predictors'' that purportedly fall short of genuine cognition. We argue that these deflationary claims need further justification. Drawing on prominent cognitive and artificial intelligence research, we critically evaluate two forms of ``Justaism'' that dismiss LLM cognition by labeling LLMs as ``just'' simplistic entities without specifying or substantiating the critical capacities these models supposedly lack. Our analysis highlights the need for a more measured discussion of LLM cognition, to better inform future research and the development of artificial intelligence."
}