Papers by Gal Shachaf
Learning to Retrieve Passages without Supervision (2022.naacl-main)
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| Challenge: | Dense retrievers for open domain question answering have been shown to achieve impressive performance by training on large datasets of question-passage pairs. |
| Approach: | They propose to use recurring spans to create pseudo examples for contrastive learning. |
| Outcome: | The proposed model outperforms all pretrained baselines on a wide range of ODQA datasets and is competitive with BM25, a strong sparse baseline. |