CAPER derives clause-aligned supervision via SQL AST counterfactuals to train a Clause-PRM that improves execution accuracy up to 15.3% relative and failure localization to 84.53% accuracy on BIRD and Spider.
Graph-Reward- SQL : Execution-Free Reinforcement Learning for Text-to- SQL via Graph Matching and Stepwise Reward
2 Pith papers cite this work. Polarity classification is still indexing.
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EXPO-SQL improves Text-to-SQL by using clause-level rewards derived from execution error messages and incremental clause execution instead of uniform query-level rewards.
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CAPER: Clause-Aligned Process Supervision for Text-to-SQL
CAPER derives clause-aligned supervision via SQL AST counterfactuals to train a Clause-PRM that improves execution accuracy up to 15.3% relative and failure localization to 84.53% accuracy on BIRD and Spider.
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EXPO-SQL: Execution-based Clause-level Policy Optimization for Text-to-SQL
EXPO-SQL improves Text-to-SQL by using clause-level rewards derived from execution error messages and incremental clause execution instead of uniform query-level rewards.