@inproceedings{ungless-etal-2025-amplifying,
    title = "Amplifying Trans and Nonbinary Voices: A Community-Centred Harm Taxonomy for {LLM}s",
    author = "Ungless, Eddie L.  and
      Dev, Sunipa  and
      Bennett, Cynthia L.  and
      Gulotta, Rebecca  and
      Bastings, Jasmijn  and
      Denton, Remi",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.1001/",
    pages = "20503--20535",
    ISBN = "979-8-89176-251-0",
    abstract = "We explore large language model (LLM) responses that may negatively impact the transgender and nonbinary (TGNB) community and introduce the Transing Transformers Toolkit, $T^3$, which provides resources for identifying such harmful response behaviors. The heart of $T^3$ is a community-centred taxonomy of harms, developed in collaboration with the TGNB community, which we complement with, amongst other guidance, suggested heuristics for evaluation. To develop the taxonomy, we adopted a multi-method approach that included surveys and focus groups with community experts. The contribution highlights the importance of community-centred approaches in mitigating harm, and outlines pathways for LLM developers to improve how their models handle TGNB-related topics."
}