@inproceedings{vazhentsev-etal-2025-token,
    title = "Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models",
    author = "Vazhentsev, Artem  and
      Rvanova, Lyudmila  and
      Lazichny, Ivan  and
      Panchenko, Alexander  and
      Panov, Maxim  and
      Baldwin, Timothy  and
      Shelmanov, Artem",
    editor = "Chiruzzo, Luis  and
      Ritter, Alan  and
      Wang, Lu",
    booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.naacl-long.113/",
    pages = "2246--2262",
    ISBN = "979-8-89176-189-6"
}