Papers with ATL
Active Learning for Rumor Identification on Social Media (2021.findings-emnlp)
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| Challenge: | Existing methods for rumor tracking depend on a significant amount of labeled data. |
| Approach: | They propose an Active-Transfer Learning strategy to identify rumors with limited amount of annotated data. |
| Outcome: | The proposed approach achieves faster convergence in terms of the F-score while requiring fewer annotated samples (42% of the whole dataset for the best model). |