3 papers
cs.CL2024
Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis
Wenhao Zhu, Hongyi Liu, Qingxiu Dong +5
Large language models (LLMs) have demonstrated remarkable potential in handling multilingual machine translation (MMT). In this paper, we systematically investigate the advantages…
cs.CL2024
Lost in the Source Language: How Large Language Models Evaluate the Quality of Machine Translation
Xu Huang, Zhirui Zhang, Xiang Geng +3
This study investigates how Large Language Models (LLMs) leverage source and reference data in machine translation evaluation task, aiming to better understand the mechanisms behin…
cs.CL2024
Eliciting the Translation Ability of Large Language Models via Multilingual Finetuning with Translation Instructions
Jiahuan Li, Hao Zhou, Shujian Huang +2
Large-scale Pretrained Language Models (LLMs), such as ChatGPT and GPT4, have shown strong abilities in multilingual translations, without being explicitly trained on parallel corp…