Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis

Large language models (LLMs) have demonstrated remarkable potential in handling multilingual machine translation (MMT).In this paper, we systematically investigate the advantages and challenges of LLMs for MMT by answering two questions: 1) How well do LLMs perform in translating massive languages?2) Which factors affect LLMs' performance in translation?We thoroughly evaluate eight popular LLMs, including ChatGPT and GPT-4.Our empirical results show that translation capabilities of LLMs are continually involving.GPT-4 has beat the strong supervised baseline NLLB in 40.91% of translation directions but still faces a large gap towards the commercial translation system like Google Translate, especially on…

• NS
  National Science Foundation
• NN
  National Natural Science Foundation of China
• NU
  Nanjing University