Papers with dense Lexical Model Λ
Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One? (2022.findings-emnlp)
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Xilun Chen, Kushal Lakhotia, Barlas Oguz, Anchit Gupta, Patrick Lewis, Stan Peshterliev, Yashar Mehdad, Sonal Gupta, Wen-tau Yih
| Challenge: | Existing sparse retrievers lack the ability to match salient phrases and rare entities in the query. |
| Approach: | They introduce a dense Lexical Model that can be trained to imitate a sparse one. |
| Outcome: | The proposed model outperforms sparse retrievers on a range of tasks including five question answering datasets and the MS MARCO passage retrieval. |