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Lexical diversity and translation literalness in machine translation: a comparative study of pretrained, fine-tuned, and few-shot approaches
This paper presents a comparative study of neural machine translation (MT) models and large language models, emphasizing translation literalness, lexical diversity, and translation quality. We evaluate open-source neural machine translation (NMT) models, LLaMa 3.1 Instruct, and GPT-4o across nine language pairs in pr...