mlsanityData to 7 Oct 2026

CoE-SQL: In-Context Learning for Multi-Turn Text-to-SQL with Chain-of-Editions

arXiv 2405.02712 ↗First posted 4 May 2024cs.CLcited by 13

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Abstract (arXiv)

Recently, Large Language Models (LLMs) have been demonstrated to possess impressive capabilities in a variety of domains and tasks. We investigate the issue of prompt design in the multi-turn text-to-SQL task and attempt to enhance the LLMs' reasoning capacity when generating SQL queries. In the conversational context, the current SQL query can be modified from the preceding SQL query with only a few operations due to the context dependency. We introduce our method called CoE-SQL which can prompt LLMs to generate the SQL query based on the previously generated SQL query with an edition chain. We also conduct extensive ablation studies to determine the optimal configuration of our approach. Our approach outperforms different in-context learning baselines stably and achieves state-of-the-art performances on two benchmarks SParC and CoSQL using LLMs, which is also competitive to the SOTA fine-tuned models.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 24 of its 29 references that are in the map. First posted on arXiv 4 May 2024.

Builds on

24 of 29 references.

References · 24

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  4. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  5. 2023Teaching Large Language Models to Self-Debugcited by 963
  6. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 679
  7. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 465
  8. 2021PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Modelscited by 402
  9. 2019CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databasescited by 180
  10. 2019SParC: Cross-Domain Semantic Parsing in Contextcited by 141
  11. 2017SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learningcited by 135
  12. 2022RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQLcited by 85
12 more
  1. 2019Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questionscited by 80
  2. 2020Grounded Adaptation for Zero-shot Executable Semantic Parsingcited by 76
  3. 2023ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thoughtcited by 65
  4. 2023Enhancing Few-shot Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategiescited by 44
  5. 2020IGSQL: Database Schema Interaction Graph Based Neural Model for Context-Dependent Text-to-SQL Generationcited by 29
  6. 2022HIE-SQL: History Information Enhanced Network for Context-Dependent Text-to-SQL Semantic Parsingcited by 26
  7. 2023Text-to-SQL Error Correction with Language Models of Codecited by 21
  8. 2022STAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL Parsingcited by 19
  9. 2020Tracking Interaction States for Multi-Turn Text-to-SQL Semantic Parsingcited by 18
  10. 2021Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsingcited by 15
  11. 2021Decoupled Dialogue Modeling and Semantic Parsing for Multi-Turn Text-to-SQLcited by 13
  12. 2022CQR-SQL: Conversational Question Reformulation Enhanced Context-Dependent Text-to-SQL Parserscited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 7; 2026: 4.

13 papers.

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  1. 2024A Survey on Employing Large Language Models for Text-to-SQL Taskscited by 67
  2. 2024A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?cited by 54
  3. 2025MTSQL-R1: Towards Long-Horizon Multi-Turn Text-to-SQL via Agentic Trainingcited by 5
  4. 2025Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunitiescited by 4
  5. 2025SAFENLIDB: A Privacy-Preserving Safety Alignment Framework for LLM-based Natural Language Database Interfacescited by 4
  6. 2026Learning to Retrieve: Dual-Level Long-Term Memory for Text-to-SQL Agentscited by 4
  7. 2025Abacus-SQL: A Text-to-SQL System Empowering Cross-Domain and Open-Domain Database Retrievalcited by 3
  8. 2026SQL-ASTRA: Alleviating Sparse Feedback in Agentic SQL via Column-Set Matching and Trajectory Aggregationcited by 3
  9. 2025MultiTEND: A Multilingual Benchmark for Natural Language to NoSQL Query Translationcited by 2
  10. 2025SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probescited by 2
  11. 2025Agentic generative AI for media content discovery at the national football leaguecited by 0
  12. 2026Track-SQL: Enhancing Generative Language Models with Dual-Extractive Modules for Schema and Context Tracking in Multi-turn Text-to-SQLcited by 0
1 more
  1. 2026ACTS-SQL: Agentic and Critic-Oriented Tree-Structured SQL Correctness with Large Language Modelscited by 0

Similar, not cited

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  1. 2023How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings
  2. 2024RB-SQL: A Retrieval-based LLM Framework for Text-to-SQL
  3. 2024Evaluating and Enhancing LLMs for Multi-turn Text-to-SQL with Multiple Question Types
  4. 2024Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models
  5. 2025SLM-SQL: An Exploration of Small Language Models for Text-to-SQL
  6. 2024PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency
  7. 2024ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQL
  8. 2023Retrieval-augmented GPT-3.5-based Text-to-SQL Framework with Sample-aware Prompting and Dynamic Revision Chain