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English(EN) Can an Old Dog Be Taught New Tricks? Taking LLMs Beyond Sentence Level Translation

大语言模型通过新的RAG系统超越句子级别翻译

研究人员开发了一个名为PAT(Pragmatic Auto-Translator)的新系统,旨在让大语言模型(LLMs)超越逐句翻译。PAT利用检索增强生成(RAG)来整合来自可比语料库真实文本的上下文,从而实现整篇文档的翻译。该系统在美国英语到拉丁美洲和墨西哥西班牙语的翻译上进行了评估,结果表明,虽然可以引导大语言模型进行超越句子级别的重述,但仍需进一步工作来提高这些重述的有效性。 AI

影响 这项研究探索了大语言模型进行整篇文档翻译的新方法,有可能提高机器翻译系统的质量和上下文感知能力。

排序理由 研究论文,详细介绍了一种大语言模型翻译的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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大语言模型通过新的RAG系统超越句子级别翻译

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研究论文,详细介绍了一种大语言模型翻译的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Alaina Brandt ·

    老狗能学新把戏吗?让大型语言模型超越句子级翻译

    Automatic translation systems, from CAT tools to MT, overwhelmingly treat translation as a sentence-by-sentence act. This paper asks whether LLMs can be moved beyond that paradigm through whole-document, corpus-informed translation. We present PAT (Pragmatic Auto-Translator), a R…