How to Detect and Prevent Hallucinations in LLM‑Powered NL2SQL Systems

This article explains the nature, types, and causes of hallucinations in large language models used for NL2SQL, reviews both unsupervised and supervised detection methods, and introduces an efficient token‑confidence based Active Sampling Detection (ASD) approach with practical deployment examples and future research directions.

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How to Detect and Prevent Hallucinations in LLM‑Powered NL2SQL Systems