Mitigating False-Negative Contexts in Multi-document Question Answering with Retrieval Marginalization (2021.emnlp-main)
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| Challenge: | Question Answering models typically use retrieval and reasoning components to identify relevant information for reasoning. |
| Approach: | They propose a retrieval parameterization method that marginalizes unanswerable queries . they show that marginalization allows a model to mitigate false negatives in annotations . |
| Outcome: | The proposed model improves on two multi-document question answering datasets and shows that marginalization improves performance. |
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Dheeru Dua, Cicero Nogueira dos Santos, Patrick Ng, Ben Athiwaratkun, Bing Xiang, Matt Gardner, Sameer Singh
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| Challenge: | Existing approaches to robustify multi-hop question answering models require expensive annotations. |
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