SDAM: Structure-Difference-Aware Memory Evolution for Complex Text-to-SQL
The episode discusses 'SDAM,' a system for improving Text-to-SQL by allowing AI to learn from its own mistakes. Hosts analyze how SDAM uses reasoning trees, contradiction detection, and schema-grounded memory to solve structural, semantic, and alignment issues in database querying.