Papers with DistDR

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Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation (2021.emnlp-main)

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Challenge: Open-domain question answering uses evidence retrieved from large corpus to answer questions . state-of-the-art approaches require intermediate evidence annotations for training . however, such intermediate annotations are expensive and methods that rely on them cannot transfer to the more common setting .
Approach: They propose an open-domain question answering approach that alternately finds evidence from an up-to-date model and encourages the model to learn the most likely evidence.
Outcome: The proposed approach improves over weak retrievers on multi-hop and single-hop benchmarks without using evidence labels.

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