JGU Mainz's Submission to the WMT25 Shared Task on LLMs with Limited Resources for Slavic Languages: MT and QA
Saadi, Hossain Shaikh, Bui, Minh Duc, Sanz-Guerrero, Mario, von der Wense, Katharina
–arXiv.org Artificial Intelligence
This paper presents the JGU Mainz submission to the WMT25 Shared Task on LLMs with Limited Resources for Slavic Languages: Machine Translation and Question Answering, focusing on Ukrainian, Upper Sorbian, and Lower Sorbian. For each language, we jointly fine-tune a Qwen2.5-3B-Instruct model for both tasks with parameter-efficient finetuning. Our pipeline integrates additional translation and multiple-choice question answering (QA) data. For Ukrainian QA, we further use retrieval-augmented generation. We also apply ensembling for QA in Upper and Lower Sorbian. Experiments show that our models outperform the baseline on both tasks.
arXiv.org Artificial Intelligence
Sep-29-2025
- Country:
- North America > United States (1.00)
- Europe > Germany
- Rheinland-Pfalz > Mainz (0.61)
- Genre:
- Research Report (0.50)
- Questionnaire & Opinion Survey (0.36)
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- Education (0.50)
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