The SETU-ADAPT Submission for WMT 24 Biomedical Shared Task

Antonio Castaldo, Maria Zafar, Prashanth Nayak, Rejwanul Haque, Andy Way, Johanna Monti

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.