Learning Prototype Representations Across Few-Shot Tasks for Event Detection (2021.emnlp-main)
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| Challenge: | Existing training data for event detection are too expensive to achieve in real applications where novel event types emerge . Typical ED systems require labeled data for each predefined event type, but only a few examples are available. |
| Approach: | They propose to introduce cross-task prototypes to model relationships between training tasks in few-shot learning for event detection. |
| Outcome: | The proposed model improves on three few-shot learning datasets. |
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