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DBRAG：面向复杂数据库查询的多表检索增强生成
原标题：DBRAG: Multi-Table Retrieval-Augmented Generation for Complex Database Queries
AI 摘要
该论文提出 DBRAG，一个面向多表问答的检索增强生成框架。它先用离线表索引检索候选表，再用查询相关行丰富表摘要并由 LLM 重排序，最后通过程序辅助推理器选择所需表并在完整内容上执行操作。在 Spider、GeoQuery 和 ATIS 数据集上的实验显示，该方法在表检索和多表问答上均有提升。
以上摘要由 AI 生成，可能存在误差。事实请以原文为准。
正文节选
DBRAG: Multi-Table Retrieval-Augmented Generation for Complex Database Queries Abstract Recent advancements in large language models have introduced new capabilities for reasoning over structured data, particularly through program-aided tools that can analyze tables. However, many existing methods address single-table scenarios or assume that the relevant tables are already provided. In practice, users often issue complex data exploration queries over entire databases, where relevant information
发布时间：2026-10-07 12:00
抓取时间：2026-10-07 12:18
来源机构：arXiv