Improving Pretrained Models for Zero-shot Multi-label Text Classification through Reinforced Label Hierarchy Reasoning (2021.naacl-main)
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| Challenge: | Existing zero-shot learning methods for multi-label text classification mostly learn a matching model between the feature space of text and the label space. |
| Approach: | They propose to use a graph encoder to incorporate label hierarchies to learn effective label representations on the zero-shot multi-label text classification problem. |
| Outcome: | The proposed approach outperforms previous non-pretrained methods on the zero-shot multi-label text classification task. |
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