Structured Prompting for Low-Resource Languages Reduces Vocabulary Contamination
A study on Tulu, a low-resource Dravidian language, demonstrates a structured prompting approach that reduced vocabulary contamination from 80% to 5% without fine-tuning. The method involved phonological grounding, morphological rules, negative constraints, and synthetic examples, achieving 85% grammatical accuracy.
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A study on Tulu, a low-resource Dravidian language, demonstrates a structured prompting approach that reduced vocabulary contamination from 80% to 5% without fine-tuning. The method involved phonological grounding, morphological rules, negative constraints, and synthetic examples, achieving 85% grammatical accuracy.
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