@inproceedings{hojer-etal-2025-research,
    title = "Research Community Perspectives on ``Intelligence'' and Large Language Models",
    author = "H{\o}jer, Bertram  and
      Thorn Jakobsen, Terne Sasha  and
      Rogers, Anna  and
      Heinrich, Stefan",
    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/corrections-2025-08/2025.findings-acl.1324/",
    doi = "10.18653/v1/2025.findings-acl.1324",
    pages = "25796--25812",
    ISBN = "979-8-89176-256-5",
    abstract = "Despite the widespread use of `artificial intelligence' (AI) framing in Natural Language Processing (NLP) research, it is not clear what researchers mean by ``intelligence''. To that end, we present the results of a survey on the notion of ``intelligence'' among researchers and its role in the research agenda. The survey elicited complete responses from 303 researchers from a variety of fields including NLP, Machine Learning (ML), Cognitive Science, Linguistics, and Neuroscience.We identify 3 criteria of intelligence that the community agrees on the most: generalization, adaptability, {\&} reasoning.Our results suggests that the perception of the current NLP systems as ``intelligent'' is a minority position (29{\%}).Furthermore, only 16.2{\%} of the respondents see developing intelligent systems as a research goal, and these respondents are more likely to consider the current systems intelligent."
}