ADAPT Enhances Explainable Neural Machine Translation with adaptNMT

01 September 2023

ADAPT academics featured recently in Slator for their work with adaptNMT, an innovative open-source solution which aims to enhance transparency and understanding in neural machine translation while fostering sustainable development

Séamus Lankford (Dublin City University), Haithem Afli (Munster Technological University), and Andy Way (Dublin City University) described adaptNMT in their recent research paper as “a tool tailored for both technical and non-technical users in the field of machine translation (MT). It is built upon the widely adopted OpenNMT framework and offers a platform for creating, training, and deploying RNN and Transformer NMT models.”

The launch of adaptNMT marks a step towards achieving explainable neural machine translation (XNMT) while also addressing the growing concern of environmental sustainability in AI model development. AdaptNMT is freely available on GitHub at

Read the full article on Slator here.