Papers with long sentence translation

2 papers
Sentence Concatenation Approach to Data Augmentation for Neural Machine Translation (2021.naacl-srw)

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Challenge: Neural machine translation is known to show poor performance at long sentence translations . however, when the sentence length exceeds a certain value, the quality of NMT becomes inferior to that of statistical machine translation.
Approach: They propose a method that uses given parallel corpora as train data to generate long sentences by concatenating two sentences at random.
Outcome: The proposed method improves translation quality more when combined with back-translation.
Modeling Concentrated Cross-Attention for Neural Machine Translation with Gaussian Mixture Model (2021.findings-emnlp)

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Challenge: Dot-product attention only considers the pair-wise correlation between words, resulting in dispersion when dealing with long sentences and neglecting source neighboring relationships.
Approach: They propose to model concentrated attention in cross-attention using a Gaussian Mixture Model to model cross- attention in a language model.
Outcome: Experiments on three datasets show that the proposed method outperforms the baseline and has significant improvement on alignment quality, N-gram accuracy, and long sentence translation.

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