Papers by Gyutae Park
Dynamic Label Name Refinement for Few-Shot Dialogue Intent Classification (2025.acl-short)
Copied to clipboard
| Challenge: | Current intent classification systems face significant challenges due to the vast number of possible intents and significant semantic overlap among similar intent classes. |
| Approach: | They propose a dynamic label refinement method that retrieves relevant examples for a test input and leverages a large language model to dynamically refine intent labels based on semantic understanding. |
| Outcome: | The proposed method resolves confusion between semantically similar intents and generates more interpretable intent labels. |