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2025 EMNLP EMNLP 2025

JGU Mainz’s Submission to the WMT25 Shared Task on LLMs with Limited Resources for Slavic Languages: MT and QA

AbstractThis 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.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing

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