How DDAIR you? Disambiguated Data Augmentation for Intent Recognition (2026.eacl-short)
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| Challenge: | Large Language Models (LLMs) produce ambiguous examples with regard to untargeted classes. |
| Approach: | They propose to use a sentence transformer to detect ambiguous augmented examples generated by Large Language Models for intent recognition. |
| Outcome: | The proposed method improves the quality of augmented data generated by large language models in low-resource scenarios. |
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