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    <abstract>Negation is a common linguistic phenomenon. Yet language models face challenges with negation in many natural language understanding tasks such as question answering and natural language inference. In this paper, we experiment with seamless strategies that incorporate affirmative interpretations (i.e., paraphrases without negation) to make models more robust against negation. Crucially, our affirmative interpretations are obtained automatically. We show improvements with CondaQA, a large corpus requiring reasoning with negation, and five natural language understanding tasks.</abstract>
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%0 Conference Proceedings
%T Paraphrasing in Affirmative Terms Improves Negation Understanding
%A Rezaei, MohammadHossein
%A Blanco, Eduardo
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F rezaei-blanco-2024-paraphrasing
%X Negation is a common linguistic phenomenon. Yet language models face challenges with negation in many natural language understanding tasks such as question answering and natural language inference. In this paper, we experiment with seamless strategies that incorporate affirmative interpretations (i.e., paraphrases without negation) to make models more robust against negation. Crucially, our affirmative interpretations are obtained automatically. We show improvements with CondaQA, a large corpus requiring reasoning with negation, and five natural language understanding tasks.
%U https://aclanthology.org/2024.acl-short.55
%P 602-615

Markdown (Informal)

[Paraphrasing in Affirmative Terms Improves Negation Understanding](https://aclanthology.org/2024.acl-short.55) (Rezaei & Blanco, ACL 2024)

• Paraphrasing in Affirmative Terms Improves Negation Understanding (Rezaei & Blanco, ACL 2024)

ACL

• MohammadHossein Rezaei and Eduardo Blanco. 2024. Paraphrasing in Affirmative Terms Improves Negation Understanding. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 602–615, Bangkok, Thailand. Association for Computational Linguistics.