Semi-supervised model adaptation for statistical machine translation

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Tagged Back-Translation (2019, methodology): “Beyond the scope of this work, we brieﬂy mention alternative techniques leveraging monolingual data, like forward translation (Uefﬁng et al., 2007; Kim and Rush, 2016), or source copying (Currey et al., 2017).”
Dual Learning for Machine Translation (2016, methodology): “ the target language are used to train a language model, which is then integrated with the MT models trained from parallel bilingual corpora to improve the translation quality. In the second category [16, 12], pseudo bilingual sentence pairs are generated from monolingual data by using the translati”
Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization (2018, methodology): “Such an idea has been used both in NMT (Sennrich, Haddow, and Birch 2016) and statistical machine translation (Bertoldi and Federico 2009; Lambert et al. 2011; Ueffing, Haffari, and Sarkar 2007).”
Domain Adaptation for Statistical Machine Translation with Monolingual Resources (2009, methodology): “Ueffing et al. (2007) proposed several elaborate adap- tation methods relying on additional bilingual data synthesized from the development or test set.”
Improving Translation Model by Monolingual Data (2011, methodology): “Ueffing et al. (2007) used a boot-strapping technique to extend translation models using monolingual data.”