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

Text generation has become more accessible than ever, and the increasing interest in these
systems, especially those using large language models, has spurred an increasing number …

Previous work mainly focuses on improving cross-lingual transfer for NLU tasks with a
multilingual pretrained encoder (MPE), or improving the performance on supervised …

Modern code review is a critical quality assurance process that is widely adopted in both
industry and open source software environments. This process can help newcomers learn …

Automated Program Repair (APR) is defined as the process of fixing a bug/defect in the
source code, by an automated tool. APR tools have recently experienced promising results …

Stance detection determines whether the author of a text is in favor of, against or neutral to a
specific target and provides valuable insights into important events such as legalization of …

This paper addresses the task of contextual translation using multi-segment models.
Specifically we show that increasing model capacity further pushes the limits of this …

Neural machine translation (NMT) systems have greatly improved the quality available from
machine translation (MT) compared to statistical machine translation (SMT) systems …

Stance detection aims to determine the position of an author toward a target and provides
insights into people's views on controversial topics such as marijuana legalization. Despite …

Domain Adaptation is widely used in practical applications of neural machine translation,
which aims to achieve good performance on both the general-domain and in-domain …