XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL

• URL: http://arxiv.org/abs/2507.04701v1
• Date: Mon, 07 Jul 2025 06:50:46 GMT
• Title: XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL
• Authors: Yifu Liu, Yin Zhu, Yingqi Gao, Zhiling Luo, Xiaoxia Li, Xiaorong Shi, Yuntao Hong, Jinyang Gao, Yu Li, Bolin Ding, Jingren Zhou,
• Abstract summary: We present XiYan-, an innovative framework effectively generating and utilizing multiplesql candidates.<n>Overall, XiYan- achieves a new SOTA performance of 75.63% on the notable BIRD benchmark.<n>It also attains SOTA performance on the Spider test set with an accuracy of 89.65%.
• Score: 48.45491386478092
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: To leverage the advantages of LLM in addressing challenges in the Text-to-SQL task, we present XiYan-SQL, an innovative framework effectively generating and utilizing multiple SQL candidates. It consists of three components: 1) a Schema Filter module filtering and obtaining multiple relevant schemas; 2) a multi-generator ensemble approach generating multiple highquality and diverse SQL queries; 3) a selection model with a candidate reorganization strategy implemented to obtain the optimal SQL query. Specifically, for the multi-generator ensemble, we employ a multi-task fine-tuning strategy to enhance the capabilities of SQL generation models for the intrinsic alignment between SQL and text, and construct multiple generation models with distinct generation styles by fine-tuning across different SQL formats. The experimental results and comprehensive analysis demonstrate the effectiveness and robustness of our framework. Overall, XiYan-SQL achieves a new SOTA performance of 75.63% on the notable BIRD benchmark, surpassing all previous methods. It also attains SOTA performance on the Spider test set with an accuracy of 89.65%.

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