Apr 14, 2021 · We concentrate on robust approaches to domain adaptation for NMT, particularly where a system may need to translate across multiple domains.

We survey approaches to domain adaptation for NMT, particularly where a system may need to translate across multiple domains. We divide techniques into those ...

We survey approaches to domain adaptation for NMT, particularly where a system may need to translate across multiple domains. We divide techniques into those ...

Domain Adaptation and Multi-Domain Adaptation forNeural Machine Translation: A SurveyDanielle Saundersds636@cantab.ac.ukCambridge University Engineering ...

A comprehensive survey of the state-of-the-art domain adaptation techniques for NMT is given, which leverages both out- of-domain parallel corpora as well ...

Neural machine translation (NMT) is a deep learning based approach for machine translation, which yields the state-of-the-art translation performance in ...

We show that iterative fine-tuning can achieve strong performance over multiple related domains, and that Elastic Weight Consolidation can be used to mitigate.

In this paper, we give a comprehensive survey of the state-of-the-art domain adaptation techniques for MT.

Domain adaptation for neural machine translation ... Finally we demonstrate the benefit of multi-domain adaptation approaches for other lines of NMT research.

Jun 1, 2018 · A Survey of Domain Adaptation for Neural Machine Translation ... Multilingual and multi-domain adaptation for neural machine translation.