弥合开源软件中语言鸿沟的LLM驱动文档翻译
Towards Bridging Language Gaps in OSS with LLM-Driven Documentation Translation
AI总结：
本文研究了LLM在开源技术文档翻译中的能力与挑战，通过实证评估发现LLM能提供准确的语义翻译，但结构和技术内容的保持存在困难。
摘要：
尽管开源社区吸引了全球各地的贡献者，但只有少数开源软件仓库提供除英语以外的其他语言的必要文档，如ReadMe或CONTRIBUTING文件。最近，大型语言模型（LLMs）在各种软件工程任务中展示了卓越的能力。我们还看到了LLMs在其他领域和情境中的翻译进展。尽管有这些进展，关于LLMs在翻译开源技术文档方面的能力知之甚少，这些文档通常混合了自然语言、代码、URL和Markdown格式。为了更好地理解LLMs在支持开源技术文档翻译中的需求和潜力，我们对两个强大的大型语言模型（OpenAI ChatGPT 4和Anthropic Claude）的翻译活动和翻译能力进行了实证评估。我们发现，翻译活动通常是社区驱动的，且在较大的仓库中最为频繁。对LLM作为翻译者和评估者的性能比较表明，LLMs可以提供准确的语义翻译，但在保持结构和技术内容方面可能遇到困难。这些发现突显了LLM辅助文档国际化的前景和挑战，并为自动化LLM驱动的支持创建和维护开源文档提供了基础。
英文摘要：
While open source communities attract diverse contributors across the globe, only a few open source software repositories provide essential documentation, such as ReadMe or CONTRIBUTING files, in languages other than English. Recently, large language models (LLMs) have demonstrated remarkable capabilities in a variety of software engineering tasks. We have also seen advances in the use of LLMs for translations in other domains and contexts. Despite this progress, little is known regarding the capabilities of LLMs in translating open-source technical documentation, which is often a mixture of natural language, code, URLs, and markdown formatting. To better understand the need and potential for LLMs to support translation of technical documentation in open source, we conducted an empirical evaluation of translation activity and translation capabilities of two powerful large language models (OpenAI ChatGPT 4 and Anthropic Claude). We found that translation activity is often community-driven and most frequent in larger repositories. A comparison of LLM performance as translators and evaluators of technical documentation suggests LLMs can provide accurate semantic translations but may struggle preserving structure and technical content. These findings highlight both the promise and the challenges of LLM-assisted documentation internationalization and provide a foundation towards automated LLM-driven support for creating and maintaining open source documentation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
