Sepideh Entezari Maleki

Confidence Estimation for Text-to-SQL in Large Language Models

Confidence estimation for text-to-SQL aims to assess the reliability of model-generated SQL queries without having access to gold answers. We study this problem in the context of large language models (LLMs), where access to model weights and gradients is often constrained. We explore both black-box