@inproceedings{lonke-etal-2025-anthroset,
    title = "{A}nthro{S}et: a Challenge Dataset for Anthropomorphic Language Detection",
    author = "Lonke, Dorielle  and
      Bloem, Jelke  and
      Sommerauer, Pia",
    editor = "Przyby{\l}a, Piotr  and
      Shardlow, Matthew  and
      Colombatto, Clara  and
      Inie, Nanna",
    booktitle = "Proceedings of Interdisciplinary Workshop on Observations of Misunderstood, Misguided and Malicious Use of Language Models",
    month = sep,
    year = "2025",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd., Shoumen, Bulgaria",
    url = "https://preview.aclanthology.org/master-new-author-system-docs/2025.ommm-1.3/",
    pages = "27--39",
    abstract = "This paper addresses the challenge of detecting anthropomorphic language in AI research. We introduce AnthroSet, a novel dataset of 600 manually annotated utterances covering various linguistic structures. Through the evaluation of two current approaches for anthropomorphism and atypical animacy detection, we highlight the limitations of a masked language model approach, arising from masking constraints as well as increasingly anthropomorphizing AI-related terminology. Our findings underscore the need for more targeted methods and a robust definition of anthropomorphism."
}