CHEF in the Language Kitchen: A Generative Data Augmentation Leveraging Korean Morpheme Ingredients (2023.emnlp-main)
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| Challenge: | Korean morphological variations present unique opportunities and challenges in natural language processing (NLP), necessitating an advanced understanding of morpheme-based sentence construction. |
| Approach: | They propose a method to replicate morphological transformations inherent in Korean sentences based on lexical and functional morphemes through generative data augmentation. |
| Outcome: | The proposed method improves performance in Korean multiple classification datasets without incurring external data usage. |
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