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AbstractThe ability of machine translation (MT) models to correctly place markup is crucial to generating high-quality translations of formatted input. This paper compares two commonly used methods of representing markup …...

AbstractFine-grained control of machine translation (MT) outputs along multiple attributes is critical for many modern MT applications and is a requirement for gaining users’ trust. A standard approach for exerting …...

AbstractRecent studies show that the attention heads in Transformer are not equal. We relate this phenomenon to the imbalance training of multi-head attention and the model dependence on specific heads. …...

AbstractWord-level quality scores on input source sentences can provide useful feedback to an end-user when translating into an unfamiliar target language. Recent approaches either require training special word-scoring models based …...