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 …

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 …

The rise in malicious usage of large language models, such as fake content creation and
academic plagiarism, has motivated the development of approaches that identify AI …

Multiple entities in a document generally exhibit complex inter-sentence relations, and
cannot be well handled by existing relation extraction (RE) methods that typically focus on …

Messages in human conversations inherently convey emotions. The task of detecting
emotions in textual conversations leads to a wide range of applications such as opinion …

Large language models (LLMs) are competitive with the state of the art on a wide range of
sentence-level translation datasets. However, their ability to translate paragraphs and …

Though machine translation errors caused by the lack of context beyond one sentence have
long been acknowledged, the development of context-aware NMT systems is hampered by …

Radiology report generation (RRG) aims to describe automatically a radiology image with
human-like language and could potentially support the work of radiologists, reducing the …

Despite the progress made in sentence-level NMT, current systems still fall short at
achieving fluent, good quality translation for a full document. Recent works in context-aware …

Purpose As the tourism industry becomes more vital for the success of many economies
around the world, the importance of technology in tourism grows daily. Alongside increasing …