The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …

Natural language processing (NLP) is a subfield of artificial intelligence that focuses on
enabling computers to understand and process human languages. In the last five years, we …

While machine translation has traditionally relied on large amounts of parallel corpora, a
recent research line has managed to train both Neural Machine Translation (NMT) and …

Abstract Machine translation (MT) is an important sub-field of natural language processing
that aims to translate natural languages using computers. In recent years, end-to-end neural …

Developing artificial learning systems that can understand and generate natural language
has been one of the long-standing goals of artificial intelligence. Recent decades have …

Translation to or from low-resource languages LRLs poses challenges for machine
translation in terms of both adequacy and fluency. Data augmentation utilizing large …

Abstract Machine translation is an important and challenging task that aims at automatically
translating natural language sentences from one language into another. Recently …

While neural conversation models have shown great potentials towards generating
informative and engaging responses via introducing external knowledge, learning such a …

The scarcity of large parallel corpora is an important obstacle for neural machine translation.
A common solution is to exploit the knowledge of language models (LM) trained on …

Neural approaches have achieved state-of-the-art accuracy on machine translation but
suffer from the high cost of collecting large scale parallel data. Thus, a lot of research has …