@inproceedings{labate-cozman-2026-semantic,
    title = "Semantic adapters in text-to-{SQL} for low-resource languages: the importance of semantic information",
    author = "Labate, Anton Bulle  and
      Cozman, Fabio Gagliardi",
    editor = "Souza, Marlo  and
      de-Dios-Flores, Iria  and
      Santos, Diana  and
      Freitas, Larissa  and
      Souza, Jackson Wilke da Cruz  and
      Ribeiro, Eug{\'e}nio",
    booktitle = "Proceedings of the 17th International Conference on Computational Processing of {P}ortuguese ({PROPOR} 2026) - Vol. 1",
    month = apr,
    year = "2026",
    address = "Salvador, Brazil",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-dnd/2026.propor-1.106/",
    pages = "1032--1037",
    ISBN = "979-8-89176-387-6",
    abstract = "This paper investigates whether injecting semantic structural knowledge of low-resource or unfamiliar languages into Large Language Models (LLMs) enhances performance on downstream Text-to-SQL tasks. We evaluate our approach on Galician, a Romance low-resource language, and, to demonstrate its generality, also on Guarani, a (very) low-resource language of an entirely distinct linguistic profile. Our empirical results show that semantically-aware models consistently outperform baselines across all benchmark metrics."
}