Replacing Training with Memory: Listwise Selection for Text-to-SQL
This work proposes a fine-tuning-free listwise selector that improves selection accuracy while maintaining efficiency and compatibility with existing large language models, and builds reusable structured memories instead of learning selection behavior as model parameters.