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LLM-based Translation for Latin: Summaries Improve Machine Translation

Year: 2025

Type: conference-paper

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.

Source: Zurich Open Repository and Archive (University of Zurich)

DOI: 10.5167/uzh-279356

Authors: Fischer, Dominic P, Volk, Martin

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6967449449

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