Reference-based Weak Supervision for Answer Sentence Selection using Web Data (2021.findings-emnlp)
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| Challenge: | Existing solutions for QA use weakly-supervised data from Web. |
| Approach: | They propose a data pipeline that harvests weakly-supervised answer sentences from Web data . they train TANDA models, which are the state of the art for AS2 . |
| Outcome: | The proposed pipeline improves on three different datasets and sets the state-of-the-art models to P@1=90.1% and MAP=92.9%. |
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