6 papers
Design of an Open-Source Architecture for Neural Machine Translation
Séamus Lankford, Haithem Afli, Andy Way
adaptNMT is an open-source application that offers a streamlined approach to the development and deployment of Recurrent Neural Networks and Transformer models. This application is…
adaptMLLM: Fine-Tuning Multilingual Language Models on Low-Resource Languages with Integrated LLM Playgrounds
Séamus Lankford, Haithem Afli, Andy Way
The advent of Multilingual Language Models (MLLMs) and Large Language Models has spawned innovation in many areas of natural language processing. Despite the exciting potential of…
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…
Human Evaluation of English--Irish Transformer-Based NMT
Séamus Lankford, Haithem Afli, Andy Way
In this study, a human evaluation is carried out on how hyperparameter settings impact the quality of Transformer-based Neural Machine Translation (NMT) for the low-resourced Engli…
Machine Translation in the Covid domain: an English-Irish case study for LoResMT 2021
Séamus Lankford, Haithem Afli, Andy Way
Translation models for the specific domain of translating Covid data from English to Irish were developed for the LoResMT 2021 shared task. Domain adaptation techniques, using a Co…
Federated Split Learning with Only Positive Labels for resource-constrained IoT environment
Praveen Joshi, Chandra Thapa, Mohammed Hasanuzzaman +2
Distributed collaborative machine learning (DCML) is a promising method in the Internet of Things (IoT) domain for training deep learning models, as data is distributed across mult…