Papers with D-LCNMT

1 papers
Disambiguated Lexically Constrained Neural Machine Translation (2023.findings-acl)

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Challenge: Current approaches to LCNMT assume that pre-specified lexicon constraints are contextually appropriate.
Approach: They propose a framework that disambiguates constraints based on contexts at first and integrates them into LCNMT.
Outcome: The proposed approach outperforms baseline approaches on benchmark datasets and comprehensive experiments in multiple target constraints.

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