Papers with self-correction approaches

2 papers
Boosting Text-to-SQL through Multi-grained Error Identification (2025.coling-main)

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Challenge: Existing methods for error identification often overlook validation of generated results . text-to-SQL is a technology that converts natural language questions into executable SQL queries .
Approach: They propose to integrate a multi-grained error identification method into existing methods to detect SQL errors.
Outcome: The proposed method can be integrated as a plugin into various methods, providing effective error identification and correction capabilities.
SHARE: An SLM-based Hierarchical Action CorREction Assistant for Text-to-SQL (2025.acl-long)

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Challenge: Existing approaches to self-correct text-to-SQL fail to demonstrate underlying reasoning path . authors propose **SHARE**, a self-revolution assistant for text-based error correction .
Approach: They propose a "SHARE" assistant that enables LLMs to perform more precise error localization and efficient correction.
Outcome: The proposed assistant performs more precise error localization and efficient correction for monolithic SQL queries.

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