Papers with MR-P

1 papers
MR-P: A Parallel Decoding Algorithm for Iterative Refinement Non-Autoregressive Translation (2022.findings-acl)

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Challenge: Non-autoregressive neural machine translation models remove dependency between tokens in the target sentence and generate all tokens on parallel .
Approach: They propose a non-autoregressive neural machine translation model that decodes with the Mask-Predict algorithm which iteratively refines the output.
Outcome: The proposed algorithm increases the performance of the WMT’14 translation task by 1.39 points.

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