@inproceedings{arora-etal-2023-adapt,
    title = "Adapt and Decompose: Efficient Generalization of Text-to-{SQL} via Domain Adapted Least-To-Most Prompting",
    author = "Arora, Aseem  and
      Bhaisaheb, Shabbirhussain  and
      Nigam, Harshit  and
      Patwardhan, Manasi  and
      Vig, Lovekesh  and
      Shroff, Gautam",
    editor = "Hupkes, Dieuwke  and
      Dankers, Verna  and
      Batsuren, Khuyagbaatar  and
      Sinha, Koustuv  and
      Kazemnejad, Amirhossein  and
      Christodoulopoulos, Christos  and
      Cotterell, Ryan  and
      Bruni, Elia",
    booktitle = "Proceedings of the 1st GenBench Workshop on (Benchmarking) Generalisation in NLP",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.genbench-1.3/",
    doi = "10.18653/v1/2023.genbench-1.3",
    pages = "25--47"
}