SemanticAgent introduces a three-stage semantic analysis, synthesis, and verification process that produces higher-quality text-to-SQL training data than prior execution-only methods.
SING-SQL: A synthetic data generation framework for in-domain text-to-SQL translation
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
STAGE generates source-grounded text-to-JSON training data via spreadsheet validation, raising Qwen3-4B exact match from 31.37% to 74.27% on the 851-example STAGE-Eval benchmark.
citing papers explorer
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SemanticAgent: A Semantics-Aware Framework for Text-to-SQL Data Synthesis
SemanticAgent introduces a three-stage semantic analysis, synthesis, and verification process that produces higher-quality text-to-SQL training data than prior execution-only methods.
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Source-Grounded Data Generation for Text-to-JSON Learning
STAGE generates source-grounded text-to-JSON training data via spreadsheet validation, raising Qwen3-4B exact match from 31.37% to 74.27% on the 851-example STAGE-Eval benchmark.