LLM-based Translation for Latin: Summaries Improve Machine Translation

Recent studies demonstrated that modern Large Language Models set a new state-of-the-art in translating historical Latin texts into English and German. Building upon this foundation, we investigate the impact of incorporating text summaries into prompts for LLM-based translation tasks. Having both the historical text and a modern-language summary is a typical setup for classical editions. Our findings reveal that integrating summaries significantly enhances translation accuracy and coherence.

Publication Details

Journal
Zurich Open Repository and Archive (University of Zurich)
Published
2025-05-15
DOI
https://doi.org/10.5167/uzh-279356
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

LLM-based Translation for Latin: Summaries Improve Machine Translation

Zurich Open Repository and Archive (University of Zurich)
Natural Language Processing Techniques
article

LLM-based Translation for Latin: Summaries Improve Machine Translation

article en

Abstract

Recent studies demonstrated that modern Large Language Models set a new state-of-the-art in translating historical Latin texts into English and German. Building upon this foundation, we investigate the impact of incorporating text summaries into prompts for LLM-based translation tasks. Having both the historical text and a modern-language summary is a typical setup for classical editions. Our findings reveal that integrating summaries significantly enhances translation accuracy and coherence.

Zurich Open Repository and Archive (University of Zurich)
Quality Education
Openalex Percentile: Top 74%
Natural Language Processing Techniques
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LLM-based Translation for Latin: Summaries Improve Machine Translation · Zurich Open Repository and Archive (University of Zurich) (2025) | TGRS Research Map | TGRS