Hierarchical Multi-Label Classification of Scientific Documents (2022.emnlp-main)
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| Challenge: | Automated topic classification is a useful tool for managing scientific documents in a digital collection. |
| Approach: | They propose a hierarchical multi-label text classification dataset with keyword labeling as an auxiliary task. |
| Outcome: | The proposed model achieves a Macro-F1 score of 34.57% and is publicly available. |
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