Advances and challenges in unsupervised neural machine translation
Unsupervised cross-lingual language representation initialization methods, together with
mechanisms such as denoising and back-translation, have advanced unsupervised neural …
mechanisms such as denoising and back-translation, have advanced unsupervised neural …
Finding the right recipe for low resource domain adaptation in neural machine translation
General translation models often still struggle to generate accurate translations in
specialized domains. To guide machine translation practitioners and characterize the …
specialized domains. To guide machine translation practitioners and characterize the …
[PDF][PDF] A Survey of Advances and Challenges in Unsupervised Neural Machine Translation
Unsupervised cross-lingual language representation initialization methods, together with
mechanisms such as denoising and backtranslation, have advanced unsupervised neural …
mechanisms such as denoising and backtranslation, have advanced unsupervised neural …
Transfer learning and robustness for natural language processing
D Jin - 2020 - dspace.mit.edu
Teaching machines to understand human language is one of the most elusive and long-
standing challenges in Natural Language Processing (NLP). Driven by the fast development …
standing challenges in Natural Language Processing (NLP). Driven by the fast development …