A multi-agent system based on HNC for domain-specific machine translation
Abstract Due to the lack of domain classification theory for domain-specific machine translation, the quality of translation in this area is low. We propose a domain classification system based on HNC and design a new method that can enhance domain-specific machine translation by jointly using this...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-03414-9 |
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| Summary: | Abstract Due to the lack of domain classification theory for domain-specific machine translation, the quality of translation in this area is low. We propose a domain classification system based on HNC and design a new method that can enhance domain-specific machine translation by jointly using this system with alarge language models. We propose a multi-agent system for domain-specific machine translation and a prompt generation method guided by the domain classification system. Tests of cross-lingual translation in the domains of science and technology, health and culture on open-data test sets and English-Chinese translation in the domains of politic, economy, military, and culture on human-generated test sets show our method successfully improves the capability of domain-specific machine translation of LLM. Finally, a real case is provided to demonstrate the workflow of the proposed method. |
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| ISSN: | 2045-2322 |