Work

Abacus-SQL: A Text-to-SQL System Empowering Cross-Domain and Open-Domain Database Retrieval

Year: 2025

Type: conference-paper

Abstract: The existing text-to-SQL systems have made significant progress in SQL query generation, but they still face numerous challenges.Existing systems often lack retrieval capabilities for open-domain databases, requiring users to manually filter relevant databases.Additionally, their cross-domain transferability is limited, making it challenging to accommodate diverse query requirements.To address these issues, we propose ABACUS-SQL.ABACUS-SQL utilizes database retrieval technology to accurately locate the required databases in an open-domain database environment.It also enhances the system cross-domain transfer ability through data augmentation methods.Moreover, ABACUS-SQL employs Pre-SQL and Self-debug methods, thereby enhancing the accuracy of SQL queries.Experimental results demonstrate that ABACUS-SQL performs excellently in multi-turn text-to-SQL tasks, effectively validating the approach's effectiveness.

Source: Annual Meeting of the Association for Computational Linguistics (ACL)

DOI: 10.18653/v1/2025.acl-demo.12

Authors: Keyan Xu, Dingzirui Wang, Xuanliang Zhang, Qingfu Zhu, Wanxiang Che

Institution: Harbin Institute of Technology

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: National Natural Science Foundation of China

Awards: G2565984771, G3596954764