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 …

The development of deep learning techniques has allowed Neural Machine Translation
(NMT) models to become extremely powerful, given sufficient training data and training time …

Large-scale pre-trained language model such as BERT has achieved great success in
language understanding tasks. However, it remains an open question how to utilize BERT …

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 …

Encoder-decoder models have made great progress on handwritten mathematical
expression recognition recently. However, it is still a challenge for existing methods to …

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

Abstract Machine translation (MT) is a technique that leverages computers to translate
human languages automatically. Nowadays, neural machine translation (NMT) which …

Most language models (LMs) are trained and applied in an autoregressive left-to-right
fashion, predicting the next token from the preceding ones. However, this ignores that the full …

End-to-end speech-to-text translation (E2E-ST) is becoming increasingly popular due to the
potential of its less error propagation, lower latency, and fewer parameters. Given the triplet …