Papers with semantic equivalence classifier

1 papers
Can Synthetic Translations Improve Bitext Quality? (2022.acl-long)

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Challenge: Synthetic translations have been used for a wide range of NLP tasks, but it remains unclear how they differ from naturally occurring data.
Approach: They propose to use a semantic equivalence classifier to improve bitext quality without additional bilingual supervision to replace the originals.
Outcome: The proposed samples improve bitext quality without additional bilingual supervision and are validated intrinsically and extrinsically through bilingual induction and MT tasks.

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