[r/ML] [P] Structured Prompting for Extremely Low-Resource Languages: 80% → 5% Vocabulary Contamination, No Fine-Tuning

Summary

This research introduces "Structured Prompting" to address the challenge of using frozen AI models for extremely low-resource languages like Tulu, which lack web presence and fine-tuning data. The method tackles the core problem of "vocabulary contamination," where models default to a similar, higher-resource language (e.g., Kannada) instead of the target language. By preventing models from collapsing to high-probability neighbors, it drastically reduces contamination from 80% to 5% without requiring any fine-tuning, offering a crucial solution for linguistic diversity.

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