AI RESEARCH
EvoSchema: Towards Text-to-SQL Robustness Against Schema Evolution
arXiv CS.AI
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ArXi:2603.10697v1 Announce Type: cross Neural text-to-SQL models, which translate natural language questions (NLQs) into SQL queries given a database schema, have achieved remarkable performance. However, database schemas frequently evolve to meet new requirements. Such schema evolution often leads to performance degradation for models trained on static schemas.