We explore machine translation for five Turkic language pairs: Russian-Bashkir, Russian-Kazakh, Russian-Kyrgyz, English-Tatar, English-Chuvash. Fine-tuning nllb-200-distilled-600M with LoRA on synthetic data achieved chrF++ 49.71 for Kazakh and 46.94 for Bashkir. Prompting DeepSeek-V3.2 with retrieved similar examples achieved chrF++ 39.47 for Chuvash. For Tatar, zero-shot or retrieval-based approaches achieved chrF++ 41.6, while for Kyrgyz the zero-shot approach reached 45.6. We release the dataset and the obtained weights.

翻译：本研究针对五种突厥语语言对开展机器翻译探索：俄语-巴什基尔语、俄语-哈萨克语、俄语-吉尔吉斯语、英语-鞑靼语、英语-楚瓦什语。通过在合成数据上采用LoRA微调nllb-200-distilled-600M模型，哈萨克语获得chrF++ 49.71分，巴什基尔语获得46.94分。采用检索相似示例提示DeepSeek-V3.2模型的方法，楚瓦什语取得chrF++ 39.47分。对于鞑靼语，零样本或基于检索的方法获得chrF++ 41.6分，而吉尔吉斯语的零样本方法达到45.6分。我们公开了数据集及训练所得权重。