Papers by Zhengxian Gong

2 papers
Encouraging Lexical Translation Consistency for Document-Level Neural Machine Translation (2021.emnlp-main)

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Challenge: Experimental results show document-level neural machine translation improves lexical consistency . inconsistent translations tend to confuse readers in some cases .
Approach: They propose to use a word link to obtain a document word link and an auxiliary loss function to constrain that their translation should be consistent.
Outcome: The proposed approach improves translation consistency on ChineseEnglish and EnglishFrench translation tasks.
Breaking the Corpus Bottleneck for Context-Aware Neural Machine Translation with Cross-Task Pre-training (2021.acl-long)

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Challenge: Context-aware neural machine translation (NMT) remains challenging due to the lack of large-scale document-level parallel corpora.
Approach: They propose to use large-scale parallel datasets and source-side monolingual documents to improve context-aware neural machine translation.
Outcome: The proposed model can be used to translate both sentences and documents on four translation tasks.

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