Papers by Houda Aynaou
Can LLMs Augment Low-Resource Reading Comprehension Datasets? Opportunities and Challenges (2024.acl-srw)
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| Challenge: | Large Language Models (LLMs) have demonstrated impressive zero-shot performance on a wide range of NLP tasks. |
| Approach: | They propose to use large language models to augment extractive reading comprehension datasets by fine-tuning their annotations and comparing their performance to human annotators. |
| Outcome: | The proposed model can be used to augment extractive reading comprehension datasets. |