Author

Arash Pourhabib

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#machine learning Jun 2026

Robust Active Learning for Few-Shot Example Selection in Text-to-SQL

This work proposes a stratified greedy algorithm that maximizes a heteroscedastic information-gain objective and proves that the objective is monotone and submodular under query-dependent noise, so stratified greedy selection carries a 1/2-approximation guarantee under the partition constraint.

Arash Pourhabib · arXiv.org · 0 citations