Papers by Esther Setiawan
Pushing the Limits of Low-Resource NER Using LLM Artificial Data Generation (2024.findings-acl)
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| Challenge: | Named Entity Recognition (NER) is an important task, but it requires a large amount of labeled data to perform well. |
| Approach: | They propose to use open-source Large Language Models to generate NER data with only a few labeled examples, reducing the cost of human annotations. |
| Outcome: | The proposed method significantly improves the baseline on diverse low-resource NER datasets and can be used to augment datasets with class-imbalance problems. |