Machine translation (MT) is an important task in natural language processing (NLP), as it
automates the translation process and reduces the reliance on human translators. With the …

Artificial intelligence has advanced significantly in recent years, affecting multiple aspects of
life. In particular, this has had an impact on the machine translation of texts, reducing or …

Previous work on multimodal machine translation (MMT) has focused on the way of
incorporating vision features into translation but little attention is on the quality of vision …

Transformers have dominated empirical machine learning models of natural language
processing. In this paper, we introduce basic concepts of Transformers and present key …

Writing a scientific article is a challenging task as it is a highly codified genre. Good writing
skills are essential to properly convey ideas and results of research work. Since the majority …

As a promising technology to enable effective multi-modal transmission over wireless
channels, semantic communication has attracted a lot of attention from academics and …

This paper does not aim at introducing a novel model for document-level neural machine
translation. Instead, we head back to the original Transformer model and hope to answer the …

Automatic code summarization is beneficial to software development and maintenance
since it reduces the burden of manual tasks. Currently, artificial intelligence is undergoing a …

Context-aware neural machine translation (NMT), which targets at translating sentences with
contextual information, has attracted much attention recently. A key problem for context …

Gender inclusivity in language technologies has become a prominent research topic. In this
study, we explore gender-neutral translation (GNT) as a form of gender inclusivity and a goal …