TartuNLP at WMT25 LLMs with Limited Resources for Slavic Languages Shared Task

AbstractThis paper describes the TartuNLP submission to the Upper Sorbian (hsb) and Lower Sorbian (dsb) tracks of the WMT25 LLMs with Limited Resources for Slavic Languages shared task, which jointly targets machine translation (MT) and question answering (QA). We develop a single multilingual model based on Qwen2.5-3B-Instruct by continuing pretraining on Sorbian monolingual and parallel data together with general instruction datasets, combining language acquisition and instruction-following in a single step. The resulting model delivers substantial improvements over the baseline Qwen2.5-3B-Instruct model and also achieves the highest ranking for both tasks in the hsb and dsb shared task tracks.