Thomas Lüthi
2025
SwiLTra-Bench: The Swiss Legal Translation Benchmark
Joel Niklaus
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Jakob Merane
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Luka Nenadic
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Sina Ahmadi
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Yingqiang Gao
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Cyrill A. H. Chevalley
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Claude Humbel
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Christophe Gösken
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Lorenzo Tanzi
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Thomas Lüthi
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Stefan Palombo
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Spencer Poff
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Boling Yang
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Nan Wu
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Matthew Guillod
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Robin Mamié
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Daniel Brunner
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Julio Pereyra
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Niko Grupen
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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.