mlsanityData to 14 Oct 2026

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

arXiv 2504.09824 ↗First posted 14 Apr 2025cs.CLcited by 3

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Abstract (arXiv)

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. Abacus-SQL is publicly accessible at https://huozi.8wss.com/abacus-sql/.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 15 of its 30 references that are in the map. First posted on arXiv 14 Apr 2025.

Builds on

15 of 30 references.

References · 15

  1. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,139
  2. 2023Teaching Large Language Models to Self-Debugcited by 988
  3. 2022A Survey on In-context Learningcited by 721
  4. 2023Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluationcited by 385
  5. 2019CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databasescited by 185
  6. 2019SParC: Cross-Domain Semantic Parsing in Contextcited by 144
  7. 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 120
  8. 2022RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQLcited by 85
  9. 2023ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thoughtcited by 65
  10. 2024PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistencycited by 27
  11. 2020Photon: A Robust Cross-Domain Text-to-SQL Systemcited by 26
  12. 2022N-Best Hypotheses Reranking for Text-To-SQL Systemscited by 19
3 more
  1. 2020Tracking Interaction States for Multi-Turn Text-to-SQL Semantic Parsingcited by 18
  2. 2024CoE-SQL: In-Context Learning for Multi-Turn Text-to-SQL with Chain-of-Editionscited by 13
  3. 2024Improving Demonstration Diversity by Human-Free Fusing for Text-to-SQLcited by 10

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026Fine-Grained Table Retrieval Through the Lens of Complex Queriescited by 1
  2. 2026Toward Multi-Database Query Reasoning for Text2Cyphercited by 0
  3. 2026CAPER: Clause-Aligned Process Supervision for Text-to-SQLcited by 0