Papers with Cloze-task
Unsupervised Question Answering for Fact-Checking (D19-66)
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| Challenge: | Recent Deep Learning (DL) models have achieved human-level accuracy on natural language tasks such as question-answering, natural language inference, and textual entailment. |
| Approach: | They propose an unsupervised question-answering based approach for a similar task, fact-checking. |
| Outcome: | The proposed approach achieves label accuracy of 80.2% on the development set and 80.25% on the test set. |