How do you select in-context examples for text-to-SQL prompts?
What it tests: practical ICL design for structured generation. Answer outline: select examples by SQL syntax similarity plus pattern diversity, order from simple to complex, and anchor schema context. Red flag: claiming random examples work fine.
What it tests: whether you can design a retrieval strategy for few-shot text-to-SQL that goes beyond surface-level similarity. Answer outline: retrieve candidates using the syntactic structure of the SQL query, balance semantic similarity with query-pattern diversity to cover joins, aggregations, and nested selects, order examples from simple to complex, and augment prompts with relevant database schema context. Red flag: treating examples as interchangeable or ignoring schema coverage, SQL syntax variety, and complexity ordering.
Read the original → arXiv
- #llms
- #prompt-engineering
- #text-to-sql
- #in-context-learning
- #generative-ai
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