Leveraging GPT-4 for Automatic Translation Post-Editing
While Neural Machine Translation (NMT) represents the leading approach to
Machine Translation (MT), the outputs of NMT models still require translation
post-editing to rectify errors and enhance quality, particularly under critical
settings. In this work, we formalize the task of translation post-editing with
Large Language Models (LLMs) and explore the use of GPT-4 to automatically
post-edit NMT outputs across several language pairs. Our results demonstrate
that GPT-4 is adept at translation post-editing and produces meaningful edits
even when the target language is not English. Notably, we achieve
state-of-the-art performance on WMT-22 English-Chinese, English-German,
Chinese-English and German-English language pairs using GPT-4 based
post-editing, as evaluated by state-of-the-art MT quality metrics.
646f0a74041e48e1c47062da
Vikas Raunak
admin_assigned
2023-05-26T08:11:35.877Z
5f06175e5d08220171a0ae32
https://cdn-avatars.huggingface.co/v1/production/uploads/1652484966062-5f06175e5d08220171a0ae32.jpeg
Vikas Raunak
user
vyraun
646f0a74041e48e1c47062db
Amr Sharaf
admin_assigned
2023-05-26T08:12:00.351Z
619ffce1ea7f7717b42344c6
/avatars/95bbb992cadfc8c3523ec2850d6e1e65.svg
Amr Sharaf
user
amrsharaf
646f0a74041e48e1c47062dc
Hany Hassan Awadallah
646f0a74041e48e1c47062dd
Arul Menezes
Leveraging GPT-4 for Automatic Translation Post-Editing
While Neural Machine Translation (NMT) represents the leading approach to
Machine Translation (MT), the outputs of NMT models still require translation
post-editing to rectify errors and enhance quality, particularly under critical
settings. In this work, we formalize the task of translation post-editing with
Large Language Models (LLMs) and explore the use of GPT-4 to automatically
post-edit NMT outputs across several language pairs. Our results demonstrate
that GPT-4 is adept at translation post-editing and produces meaningful edits
even when the target language is not English. Notably, we achieve
state-of-the-art performance on WMT-22 English-Chinese, English-German,
Chinese-English and German-English language pairs using GPT-4 based
post-editing, as evaluated by state-of-the-art MT quality metrics.
GPT-4 demonstrates superior performance in automatic post-editing of NMT outputs across multiple language pairs, achieving state-of-the-art results.
Neural Machine Translation Large Language Models GPT-4 translation post-editing WMT-22