Papers by Guanqiu Qin
An Effective Deployment of Contrastive Learning in Multi-label Text Classification (2023.findings-acl)
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| Challenge: | Existing studies on contrastive learning in natural language processing tasks have not explored the effectiveness of the technology. |
| Approach: | They propose five novel contrastive losses for multi-label text classification tasks that exploit the complexity of the input logic and the semantic representation space. |
| Outcome: | The proposed contrastive losses improve multi-label text classification tasks and can be adapted for multi-task tasks. |