Publications (46)
adaptNMT: an open-source, language-agnostic development environment for Neural Machine Translation
Séamus Lankford, Haithem Afli, Andy Way
adaptNMT streamlines all processes involved in the development and deployment of RNN and Transformer neural translation models. As an open-source application, it is designed for bo…
Sociotechnical Effects of Machine Translation
Joss Moorkens, Andy Way, Séamus Lankford
While the previous chapters have shown how machine translation (MT) can be useful, in this chapter we discuss some of the side-effects and risks that are associated, and how they m…
Domain Terminology Integration into Machine Translation: Leveraging Large Language Models
Yasmin Moslem, Gianfranco Romani, Mahdi Molaei +3
This paper discusses the methods that we used for our submissions to the WMT 2023 Terminology Shared Task for German-to-English (DE-EN), English-to-Czech (EN-CS), and Chinese-to-En…
Learning to Jointly Translate and Predict Dropped Pronouns with a Shared Reconstruction Mechanism
Longyue Wang, Zhaopeng Tu, Andy Way +1
Pronouns are frequently omitted in pro-drop languages, such as Chinese, generally leading to significant challenges with respect to the production of complete translations. Recentl…
gaHealth: An English-Irish Bilingual Corpus of Health Data
Séamus Lankford, Haithem Afli, Ãrla Nà Loinsigh +1
Machine Translation is a mature technology for many high-resource language pairs. However in the context of low-resource languages, there is a paucity of parallel data datasets ava…
Fine-tuning Large Language Models for Adaptive Machine Translation
Yasmin Moslem, Rejwanul Haque, Andy Way
This paper presents the outcomes of fine-tuning Mistral 7B, a general-purpose large language model (LLM), for adaptive machine translation (MT). The fine-tuning process involves ut…