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        <title>Exploring Prompt Engineering with GPT Language Models for Document-Level Machine Translation: Insights and Findings</title>
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    <abstract>This paper describes Lan-Bridge Translation systems for the WMT 2023 General Translation shared task. We participate in 2 directions: English to and from Chinese. With the emergence of large-scale models, various industries have undergone significant transformations, particularly in the realm of document-level machine translation. This has introduced a novel research paradigm that we have embraced in our participation in the WMT23 competition. Focusing on advancements in models such as GPT-3.5 and GPT-4, we have undertaken numerous prompt-based experiments. Our objective is to achieve optimal human evaluation results for document-level machine translation, resulting in our submission of the final outcomes in the general track.</abstract>
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%0 Conference Proceedings
%T Exploring Prompt Engineering with GPT Language Models for Document-Level Machine Translation: Insights and Findings
%A Wu, Yangjian
%A Hu, Gang
%Y Koehn, Philipp
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Monz, Christof
%S Proceedings of the Eighth Conference on Machine Translation
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F wu-hu-2023-exploring
%X This paper describes Lan-Bridge Translation systems for the WMT 2023 General Translation shared task. We participate in 2 directions: English to and from Chinese. With the emergence of large-scale models, various industries have undergone significant transformations, particularly in the realm of document-level machine translation. This has introduced a novel research paradigm that we have embraced in our participation in the WMT23 competition. Focusing on advancements in models such as GPT-3.5 and GPT-4, we have undertaken numerous prompt-based experiments. Our objective is to achieve optimal human evaluation results for document-level machine translation, resulting in our submission of the final outcomes in the general track.
%R 10.18653/v1/2023.wmt-1.15
%U https://aclanthology.org/2023.wmt-1.15
%U https://doi.org/10.18653/v1/2023.wmt-1.15
%P 166-169

Markdown (Informal)

[Exploring Prompt Engineering with GPT Language Models for Document-Level Machine Translation: Insights and Findings](https://aclanthology.org/2023.wmt-1.15) (Wu & Hu, WMT 2023)

• Exploring Prompt Engineering with GPT Language Models for Document-Level Machine Translation: Insights and Findings (Wu & Hu, WMT 2023)

ACL

• Yangjian Wu and Gang Hu. 2023. Exploring Prompt Engineering with GPT Language Models for Document-Level Machine Translation: Insights and Findings. In Proceedings of the Eighth Conference on Machine Translation, pages 166–169, Singapore. Association for Computational Linguistics.