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        <title>Interpreting Answers to Yes-No Questions in User-Generated Content</title>
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        <namePart type="given">Shivam</namePart>
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    <abstract>Interpreting answers to yes-no questions in social media is difficult. Yes and no keywords are uncommon, and the few answers that include them are rarely to be interpreted what the keywords suggest. In this paper, we present a new corpus of 4,442 yes-no question-answer pairs from Twitter. We discuss linguistic characteristics of answers whose interpretation is yes or no, as well as answers whose interpretation is unknown. We show that large language models are far from solving this problem, even after fine-tuning and blending other corpora for the same problem but outside social media.</abstract>
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    <identifier type="doi">10.18653/v1/2023.findings-emnlp.942</identifier>
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%0 Conference Proceedings
%T Interpreting Answers to Yes-No Questions in User-Generated Content
%A Mathur, Shivam
%A Park, Keun
%A Chinnappa, Dhivya
%A Kotamraju, Saketh
%A Blanco, Eduardo
%Y Bouamor, Houda
%Y Pino, Juan
%Y Bali, Kalika
%S Findings of the Association for Computational Linguistics: EMNLP 2023
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F mathur-etal-2023-interpreting
%X Interpreting answers to yes-no questions in social media is difficult. Yes and no keywords are uncommon, and the few answers that include them are rarely to be interpreted what the keywords suggest. In this paper, we present a new corpus of 4,442 yes-no question-answer pairs from Twitter. We discuss linguistic characteristics of answers whose interpretation is yes or no, as well as answers whose interpretation is unknown. We show that large language models are far from solving this problem, even after fine-tuning and blending other corpora for the same problem but outside social media.
%R 10.18653/v1/2023.findings-emnlp.942
%U https://aclanthology.org/2023.findings-emnlp.942
%U https://doi.org/10.18653/v1/2023.findings-emnlp.942
%P 14137-14161

Markdown (Informal)

[Interpreting Answers to Yes-No Questions in User-Generated Content](https://aclanthology.org/2023.findings-emnlp.942) (Mathur et al., Findings 2023)

• Interpreting Answers to Yes-No Questions in User-Generated Content (Mathur et al., Findings 2023)

ACL

• Shivam Mathur, Keun Park, Dhivya Chinnappa, Saketh Kotamraju, and Eduardo Blanco. 2023. Interpreting Answers to Yes-No Questions in User-Generated Content. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 14137–14161, Singapore. Association for Computational Linguistics.