2025
NAACL
NAACL 2025
Machine Translation Using Grammar Materials for LLM Post-Correction
Abstract
AbstractThis paper describes George Mason University’s submission to the AmericasNLP 2025 Shared Task on Machine Translation into Indigenous Languages. We prompt a large language model (LLM) with grammar reference materials to correct the translations produced by a finetuned Encoder-Decoder machine translation system. This system leads to improvements when translating from the indigenous languages into Spanish indicating that LLMs are capable of using grammar materials to decipher an unseen language.
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Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
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Keyword Pioneer
— grammar material
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio