Papers with vanilla MT models

1 papers
Fast Nearest Neighbor Machine Translation (2022.findings-acl)

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Challenge: Fast kNN-MT uses the entire corpus as the datastore for the nearest neighbor search . knn-MT is two-orders slower than vanilla MT models .
Approach: They propose a fast kNN-MT model that uses the entire corpus as the datastore for nearest neighbor search.
Outcome: The proposed model is two-orders faster than kNN-MT and is only two times slower than the standard model.

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