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        <title>RAGthoven at SemEval 2025 - Task 2: Enhancing Entity-Aware Machine Translation with Large Language Models, Retrieval Augmented Generation and Function Calling</title>
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    <abstract>This paper presents a system for SemEval 2025 Task 2 on entity-aware machine translation, integrating GPT-4o with Wikidata-based translations, retrieval augmented generation (RAG), and function calling. Implemented in RAGthoven, a lightweight yet powerful toolkit, our approach enriches source sentences with real-time external knowledge to address challenging or culturally specific named entities. Experiments on English-to-ten target languages show notable gains in translation quality, illustrating how LLM-based translation pipelines can leverage knowledge sources with minimal overhead. Its simplicity makes it a strong baseline for future research in entity-focused machine translation.</abstract>
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%0 Conference Proceedings
%T RAGthoven at SemEval 2025 - Task 2: Enhancing Entity-Aware Machine Translation with Large Language Models, Retrieval Augmented Generation and Function Calling
%A Skottis, Demetris
%A Karetka, Gregor
%A Suppa, Marek
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F skottis-etal-2025-ragthoven
%X This paper presents a system for SemEval 2025 Task 2 on entity-aware machine translation, integrating GPT-4o with Wikidata-based translations, retrieval augmented generation (RAG), and function calling. Implemented in RAGthoven, a lightweight yet powerful toolkit, our approach enriches source sentences with real-time external knowledge to address challenging or culturally specific named entities. Experiments on English-to-ten target languages show notable gains in translation quality, illustrating how LLM-based translation pipelines can leverage knowledge sources with minimal overhead. Its simplicity makes it a strong baseline for future research in entity-focused machine translation.
%U https://aclanthology.org/2025.semeval-1.305/
%P 2342-2351

Markdown (Informal)

[RAGthoven at SemEval 2025 - Task 2: Enhancing Entity-Aware Machine Translation with Large Language Models, Retrieval Augmented Generation and Function Calling](https://aclanthology.org/2025.semeval-1.305/) (Skottis et al., SemEval 2025)

• RAGthoven at SemEval 2025 - Task 2: Enhancing Entity-Aware Machine Translation with Large Language Models, Retrieval Augmented Generation and Function Calling (Skottis et al., SemEval 2025)

ACL

• Demetris Skottis, Gregor Karetka, and Marek Suppa. 2025. RAGthoven at SemEval 2025 - Task 2: Enhancing Entity-Aware Machine Translation with Large Language Models, Retrieval Augmented Generation and Function Calling. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), pages 2342–2351, Vienna, Austria. Association for Computational Linguistics.