Paraphrasing in Affirmative Terms Improves Negation Understanding
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866911913735094272 |
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| author | Rezaei, MohammadHossein Blanco, Eduardo |
| author_facet | Rezaei, MohammadHossein Blanco, Eduardo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_07492 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Paraphrasing in Affirmative Terms Improves Negation Understanding Rezaei, MohammadHossein Blanco, Eduardo Computation and Language 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. |
| title | Paraphrasing in Affirmative Terms Improves Negation Understanding |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2406.07492 |