@inproceedings{castaldo-etal-2024-setu,
title = "The {SETU}-{ADAPT} Submission for {WMT} 24 Biomedical Shared Task",
author = "Castaldo, Antonio and
Zafar, Maria and
Nayak, Prashanth and
Haque, Rejwanul and
Way, Andy and
Monti, Johanna",
editor = "Haddow, Barry and
Kocmi, Tom and
Koehn, Philipp and
Monz, Christof",
booktitle = "Proceedings of the Ninth Conference on Machine Translation",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.wmt-1.53",
pages = "647--653",
abstract = "This system description paper presents SETU-ADAPT{'}s submission to the WMT 2024 Biomedical Shared Task, where we participated for the language pairs English-to-French and English-to-German. Our approach focused on fine-tuning Large Language Models, using in-domain and synthetic data, employing different data augmentation and data retrieval strategies. We introduce a novel MT framework, involving three autonomous agents: a Translator Agent, an Evaluator Agent and a Reviewer Agent. We present our findings and report the quality of the outputs.",
}
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<abstract>This system description paper presents SETU-ADAPT’s submission to the WMT 2024 Biomedical Shared Task, where we participated for the language pairs English-to-French and English-to-German. Our approach focused on fine-tuning Large Language Models, using in-domain and synthetic data, employing different data augmentation and data retrieval strategies. We introduce a novel MT framework, involving three autonomous agents: a Translator Agent, an Evaluator Agent and a Reviewer Agent. We present our findings and report the quality of the outputs.</abstract>
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%0 Conference Proceedings
%T The SETU-ADAPT Submission for WMT 24 Biomedical Shared Task
%A Castaldo, Antonio
%A Zafar, Maria
%A Nayak, Prashanth
%A Haque, Rejwanul
%A Way, Andy
%A Monti, Johanna
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Koehn, Philipp
%Y Monz, Christof
%S Proceedings of the Ninth Conference on Machine Translation
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F castaldo-etal-2024-setu
%X This system description paper presents SETU-ADAPT’s submission to the WMT 2024 Biomedical Shared Task, where we participated for the language pairs English-to-French and English-to-German. Our approach focused on fine-tuning Large Language Models, using in-domain and synthetic data, employing different data augmentation and data retrieval strategies. We introduce a novel MT framework, involving three autonomous agents: a Translator Agent, an Evaluator Agent and a Reviewer Agent. We present our findings and report the quality of the outputs.
%U https://aclanthology.org/2024.wmt-1.53
%P 647-653
Markdown (Informal)
[The SETU-ADAPT Submission for WMT 24 Biomedical Shared Task](https://aclanthology.org/2024.wmt-1.53) (Castaldo et al., WMT 2024)
ACL
- Antonio Castaldo, Maria Zafar, Prashanth Nayak, Rejwanul Haque, Andy Way, and Johanna Monti. 2024. The SETU-ADAPT Submission for WMT 24 Biomedical Shared Task. In Proceedings of the Ninth Conference on Machine Translation, pages 647–653, Miami, Florida, USA. Association for Computational Linguistics.