Innovative methods improve machine translation for rare languages.
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.
Synthetic data enhances translation for low-resource Turkic languages.
Low-Rank Adaptation (LoRA) efficiently fine-tunes models.
Prompting techniques improve translation quality with limited data.
Relies on Yandex.Translate for synthetic data generation.
May introduce biases if not carefully filtered.
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