@inproceedings{ma-etal-2026-non,
    title = "Non-literal Meaning Representation in the Brain during Naturalistic Listening",
    author = "Ma, Zhengwu  and
      Huang, Yuhan  and
      Wang, Chengcheng  and
      Li, Jixing",
    editor = "Voigt, Rob  and
      Warstadt, Alex  and
      Feldman, Naomi  and
      Linzen, Tal",
    booktitle = "Proceedings of the Society for Computation in Linguistics 2026",
    month = jul,
    year = "2026",
    address = "San Diego, CA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.scil-main.22/",
    pages = "244--257",
    ISBN = "979-8-89176-412-5",
    abstract = "Naturalistic language comprehension often involves interpretations that go beyond literal meaning. In continuous narratives, literal and non-literal meanings are tightly intertwined, making them difficult to distinguish computationally. Here, we combined literal sentence representations and human-annotated non-literal interpretations for model-brain alignment. Using fMRI data recorded during passive listening to the Chinese version of The Little Prince, we annotated sentences containing non-literal meaning with human-written interpretations of their implied meaning. We then derived the literal and non-literal representations from LLaMA3.1-8B and evaluated their correspondence with neural activity using whole-brain encoding models. Literal representations aligned strongly with left-lateralized frontotemporal regions, whereas non-literal interpretations showed broader right-hemisphere involvement. Combining the two further improved encoding performance in the bilateral temporal and dorsal frontal cortices, suggesting that naturalistic comprehension engages complementary levels of meaning."
}