Search Results - "Lankford, Séamus"

adaptNMT: an open-source, language-agnostic development environment for neural machine translation by Lankford, Séamus, Afli, Haithem, Way, Andy

“…adaptNMT streamlines all processes involved in the development and deployment of RNN and Transformer neural translation models. As an open-source application,…”
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adaptMLLM: Fine-Tuning Multilingual Language Models on Low-Resource Languages with Integrated LLM Playgrounds by Lankford, Séamus, Afli, Haithem, Way, Andy

“…The advent of Multilingual Language Models (MLLMs) and Large Language Models (LLMs) has spawned innovation in many areas of natural language processing…”
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Human Evaluation of English–Irish Transformer-Based NMT by Lankford, Séamus, Afli, Haithem, Way, Andy

“…In this study, a human evaluation is carried out on how hyperparameter settings impact the quality of Transformer-based Neural Machine Translation (NMT) for…”
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Enhancing Neural Machine Translation of Low-Resource Languages: Corpus Development, Human Evaluation and Explainable AI Architectures by Lankford, Séamus

“…In the current machine translation (MT) landscape, the Transformer architecture stands out as the gold standard, especially for high-resource language pairs…”
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Leveraging LLMs for MT in Crisis Scenarios: a blueprint for low-resource languages by Lankford, Séamus, Way, Andy

“…In an evolving landscape of crisis communication, the need for robust and adaptable Machine Translation (MT) systems is more pressing than ever, particularly…”
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Neural Architecture Search using Particle Swarm and Ant Colony Optimization by Lankford, Séamus, Grimes, Diarmuid

“…Proceedings of The 28th Irish Conference on Artificial Intelligence and Cognitive Science. 2771. CEUR-WS, 2020 Neural network models have a number of…”
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Design of an Open-Source Architecture for Neural Machine Translation by Lankford, Séamus, Afli, Haithem, Way, Andy

“…In Proceedings of the 1st Workshop on Open Community-Driven Machine Translation, pages 15-20, Tampere, Finland. European Association for Machine Translation,…”
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Transformers for Low-Resource Languages: Is F\'eidir Linn by Lankford, Séamus, Afli, Haithem, Way, Andy

“…Proceedings of Machine Translation Summit XVIII: Research Track 2021 The Transformer model is the state-of-the-art in Machine Translation. However, in general,…”
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Human Evaluation of English--Irish Transformer-Based NMT by Lankford, Séamus, Afli, Haithem, Way, Andy

“…Information 2022, 13(7), 309 In this study, a human evaluation is carried out on how hyperparameter settings impact the quality of Transformer-based Neural…”
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adaptMLLM: Fine-Tuning Multilingual Language Models on Low-Resource Languages with Integrated LLM Playgrounds by Lankford, Séamus, Afli, Haithem, Way, Andy

“…Information 2023, 14(12), 638 The advent of Multilingual Language Models (MLLMs) and Large Language Models has spawned innovation in many areas of natural…”
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adaptNMT: an open-source, language-agnostic development environment for Neural Machine Translation by Lankford, Séamus, Afli, Haithem, Way, Andy

“…Language Resources and Evaluation 57, 1671-1696, (2023) adaptNMT streamlines all processes involved in the development and deployment of RNN and Transformer…”
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Machine Translation in the Covid domain: an English-Irish case study for LoResMT 2021 by Lankford, Séamus, Afli, Haithem, Way, Andy

“…Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021) Translation models for the specific domain of translating Covid…”
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How Much Data is Enough Data? Fine-Tuning Large Language Models for In-House Translation: Performance Evaluation Across Multiple Dataset Sizes by Vieira, Inacio, Allred, Will, Lankford, Séamus, Castilho, Sheila, Way, Andy

“…Decoder-only LLMs have shown impressive performance in MT due to their ability to learn from extensive datasets and generate high-quality translations…”
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gaHealth: An English-Irish Bilingual Corpus of Health Data by Lankford, Séamus, Afli, Haithem, Loinsigh, Órla Ní, Way, Andy

“…In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 6753-6758, Marseille, France. European Language Resources Association,…”
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