Hallucination Detection for LLM-based Text-to-SQL Generation via Two-Stage Metamorphic Testing
Published:Dec 24, 2025 04:04
•1 min read
•ArXiv
Analysis
The article focuses on a critical problem in LLM applications: the generation of incorrect or fabricated information (hallucinations) in the context of Text-to-SQL tasks. The proposed solution utilizes a two-stage metamorphic testing approach. This suggests a focus on improving the reliability and accuracy of LLM-generated SQL queries. The use of metamorphic testing implies a method of checking the consistency of the LLM's output under various transformations of the input, which is a robust approach to identify potential errors.
Key Takeaways
- •Addresses the problem of hallucinations in LLM-generated SQL.
- •Proposes a two-stage metamorphic testing approach.
- •Aims to improve the reliability and accuracy of Text-to-SQL generation.
Reference
“The article likely presents a novel method for detecting and mitigating hallucinations in LLM-based Text-to-SQL generation.”