@inproceedings{summers-stay-etal-2021-generative,
    title = "What Can a Generative Language Model Answer About a Passage?",
    author = "Summers-Stay, Douglas  and
      Bonial, Claire  and
      Voss, Clare",
    editor = "Fisch, Adam  and
      Talmor, Alon  and
      Chen, Danqi  and
      Choi, Eunsol  and
      Seo, Minjoon  and
      Lewis, Patrick  and
      Jia, Robin  and
      Min, Sewon",
    booktitle = "Proceedings of the 3rd Workshop on Machine Reading for Question Answering",
    month = nov,
    year = "2021",
    address = "Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2021.mrqa-1.7/",
    doi = "10.18653/v1/2021.mrqa-1.7",
    pages = "73--81",
    abstract = "Generative language models trained on large, diverse corpora can answer questions about a passage by generating the most likely continuation of the passage followed by a question/answer pair. However, accuracy rates vary depending on the type of question asked. In this paper we keep the passage fixed, and test with a wide variety of question types, exploring the strengths and weaknesses of the GPT-3 language model. We provide the passage and test questions as a challenge set for other language models."
}