Papers by Lorenzo Paletto
Label Augmentation for Zero-Shot Hierarchical Text Classification (2024.acl-long)
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| Challenge: | Hierarchical Text Classification is a difficult problem due to the lack of labeled data and the cost of manually annotating data samples. |
| Approach: | They propose a method that uses a Large Language Model to augment the deepest layer of the labels hierarchy to enhance its specificity. |
| Outcome: | The proposed method achieves state-of-the-art on four public datasets and a strong correlation between the metric values and the classification performance. |