SwiLTra-Bench：瑞士法律翻译基准
SwiLTra-Bench: The Swiss Legal Translation Benchmark
AI总结：
针对瑞士多语言法律翻译的挑战，研究提出了包含超18万对翻译数据的SwiLTra-Bench基准，评估发现前沿大模型表现最优，微调小模型虽有提升但仍不及零样本前沿模型，并推出了与人类评估高度一致的SwiLTra-Judge系统。
摘要：
在瑞士，由于该国的四种官方语言以及多语言法律文件的要求，法律翻译具有独特的重要性。然而，这一过程传统上依赖于既是法律专家又是熟练翻译的专业人员——这造成了瓶颈并影响了有效的司法获取。为了应对这一挑战，我们引入了SwiLTra-Bench，这是一个包含超过180K对齐的瑞士法律翻译对的全面多语言基准，涵盖所有瑞士语言以及英语的法律、判决摘要和新闻稿，旨在评估基于LLM的翻译系统。我们的系统评估表明，前沿模型在所有文档类型中均实现了卓越的翻译性能，而专门的翻译系统在法律方面表现突出，但在判决摘要中表现不佳。通过严格的测试和人类专家验证，我们证明，尽管微调开放SLM显著提高了其翻译质量，但它们仍落后于最佳的零样本提示前沿模型，如Claude-3.5-Sonnet。此外，我们还提出了SwiLTra-Judge，这是一个与人类专家评估最一致的专门LLM评估系统。
英文摘要：
In Switzerland legal translation is uniquely important due to the country's four official languages and requirements for multilingual legal documentation. However, this process traditionally relies on professionals who must be both legal experts and skilled translators -- creating bottlenecks and impacting effective access to justice. To address this challenge, we introduce SwiLTra-Bench, a comprehensive multilingual benchmark of over 180K aligned Swiss legal translation pairs comprising laws, headnotes, and press releases across all Swiss languages along with English, designed to evaluate LLM-based translation systems. Our systematic evaluation reveals that frontier models achieve superior translation performance across all document types, while specialized translation systems excel specifically in laws but under-perform in headnotes. Through rigorous testing and human expert validation, we demonstrate that while fine-tuning open SLMs significantly improves their translation quality, they still lag behind the best zero-shot prompted frontier models such as Claude-3.5-Sonnet. Additionally, we present SwiLTra-Judge, a specialized LLM evaluation system that aligns best with human expert assessments.
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。
