Papers by Longjie Cui

2 papers
Towards Database-Free Text-to-SQL Evaluation: A Graph-Based Metric for Functional Correctness (2025.coling-main)

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Challenge: Existing metrics for evaluating functional correctness of SQL queries are prone to false positives due to inadequately prepared test databases.
Approach: They propose a graph-based metric that uses a relational operator tree to extract rich semantic information from the logical execution plan of SQL queries and embed it into a diagram.
Outcome: The proposed method eliminates the need for extensive test database preparation and performs graph matching on unseen SQL queries.
Graph-Reward-SQL: Execution-Free Reinforcement Learning for Text-to-SQL via Graph Matching and Stepwise Reward (2025.findings-emnlp)

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Challenge: Existing methods to enhance performance of large language models (LLMs) on Text-to-SQL tasks rely on execution-based or LLM-based reward models.
Approach: They propose a reward model framework for RL-based Text-to-SQL that employs the GMNScore outcome reward model.
Outcome: The proposed reward model outperforms existing reward models on standard benchmarks including Spider and BIRD.

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