Papers with parser-independent error detection model

1 papers
Error Detection for Text-to-SQL Semantic Parsing (2023.findings-emnlp)

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Challenge: Existing text-to-SQL parsers are often over-confident, thus casting doubt on their trustworthiness when deployed for real use.
Approach: They propose a parser-independent error detection model for text-to-SQL semantic parsing . they use a language model of code as its bedrock and graph neural networks to learn structural features of queries .
Outcome: The proposed model outperforms parser-dependent uncertainty metrics on three strong parsers . it could improve the performance and usability of text-to-SQL semantic parsing, it is shown .

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