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        <title>What Can a Generative Language Model Answer About a Passage?</title>
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    <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.</abstract>
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        <date>2021-11</date>
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%0 Conference Proceedings
%T What Can a Generative Language Model Answer About a Passage?
%A Summers-Stay, Douglas
%A Bonial, Claire
%A Voss, Clare
%S Proceedings of the 3rd Workshop on Machine Reading for Question Answering
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F summers-stay-etal-2021-generative
%X 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.
%R 10.18653/v1/2021.mrqa-1.7
%U https://aclanthology.org/2021.mrqa-1.7
%U https://doi.org/10.18653/v1/2021.mrqa-1.7
%P 73-81

Markdown (Informal)

[What Can a Generative Language Model Answer About a Passage?](https://aclanthology.org/2021.mrqa-1.7) (Summers-Stay et al., MRQA 2021)

• What Can a Generative Language Model Answer About a Passage? (Summers-Stay et al., MRQA 2021)

ACL

• Douglas Summers-Stay, Claire Bonial, and Clare Voss. 2021. What Can a Generative Language Model Answer About a Passage?. In Proceedings of the 3rd Workshop on Machine Reading for Question Answering, pages 73–81, Punta Cana, Dominican Republic. Association for Computational Linguistics.