Papers by Puzhen Su
Towards Better Representations for Multi-Label Text Classification with Multi-granularity Information (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Existing studies have shown that pre-trained language models generate word frequency-oriented text representations, causing texts with different labels to be closely distributed in a narrow region, which is difficult to classify. |
| Approach: | They propose a framework to refine the text representation for multi-label text classification using contrastive learning and multi-task learning modules. |
| Outcome: | The proposed framework improves the quality of the representations and yields stable and competitive improvements. |