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Knowledge Distillation for Low-Resource Open-source Text-to-SQL Model

arXiv cs.CL · 2026-05-25 Cached

This paper proposes a knowledge-aware Text-to-SQL framework that uses knowledge distillation to improve performance in low-resource settings by constructing task-specific knowledge bases and generating synthetic training data. Experiments on seven benchmarks show substantial improvements, especially for open-source models.

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