A Novel Negative Sample Generation Method for Contrastive Learning in Hierarchical Text Classification (2025.coling-main)
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| Challenge: | Existing methods for hierarchical text classification struggle with fine-grained labels, leading to difficulties in accurate classification. |
| Approach: | They propose a hierarchical sequence ranking method for generating diverse negative samples using hierarchically structured hierarchic labels. |
| Outcome: | The proposed method achieves state-of-art (SOTA) on two datasets showing that it can distinguish between fine-grained labels and discriminate. |
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