{"total":52,"rows":[{"id":"2305.03111","title":"Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs","created":"2023-05-04","cited_by_count":688,"area":null},{"id":"2304.11015","title":"DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction","created":"2023-04-21","cited_by_count":477,"area":null},{"id":"2308.15363","title":"Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation","created":"2023-08-29","cited_by_count":385,"area":null},{"id":"2301.13808","title":"Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning","created":"2023-01-31","cited_by_count":178,"area":"lr"},{"id":"2405.16755","title":"CHESS: Contextual Harnessing for Efficient SQL Synthesis","created":"2024-05-27","cited_by_count":169,"area":null},{"id":"2507.13334","title":"A Survey of Context Engineering for Large Language Models","created":"2025-07-17","cited_by_count":126,"area":null},{"id":"2406.08426","title":"Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQL","created":"2024-06-12","cited_by_count":120,"area":null},{"id":"2301.07507","title":"Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsing","created":"2023-01-18","cited_by_count":93,"area":null},{"id":"2407.15186","title":"A Survey on Employing Large Language Models for Text-to-SQL Tasks","created":"2024-07-21","cited_by_count":67,"area":null},{"id":"2311.07989","title":"Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code","created":"2023-11-14","cited_by_count":62,"area":null},{"id":"2402.05121","title":"Large Language Model for Table Processing: A Survey","created":"2024-02-04","cited_by_count":52,"area":null},{"id":"2411.00073","title":"RSL-SQL: Robust Schema Linking in Text-to-SQL Generation","created":"2024-10-31","cited_by_count":52,"area":null},{"id":"2403.02951","title":"SQLBench: A Comprehensive Evaluation for Text-to-SQL Capabilities of Large Language Models","created":"2024-03-05","cited_by_count":32,"area":null},{"id":"2312.11988","title":"Xpert: Empowering Incident Management with Query Recommendations via Large Language Models","created":"2023-12-19","cited_by_count":22,"area":null},{"id":"2210.11888","title":"STAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL Parsing","created":"2022-10-21","cited_by_count":19,"area":null},{"id":"2410.10450","title":"KBLaM: Knowledge Base augmented Language Model","created":"2024-10-14","cited_by_count":16,"area":null},{"id":"2506.18951","title":"SWE-SQL: Illuminating LLM Pathways to Solve User SQL Issues in Real-World Applications","created":"2025-06-23","cited_by_count":16,"area":null},{"id":"2511.21402","title":"Text-to-SQL as Dual-State Reasoning: Integrating Adaptive Context and Progressive Generation","created":"2025-11-26","cited_by_count":10,"area":"lr"},{"id":"2502.12911","title":"Knapsack Optimization-based Schema Linking for LLM-based Text-to-SQL Generation","created":"2025-02-18","cited_by_count":9,"area":null},{"id":"2209.06442","title":"SUN: Exploring Intrinsic Uncertainties in Text-to-SQL Parsers","created":"2022-09-14","cited_by_count":7,"area":null},{"id":"2210.12674","title":"Towards Generalizable and Robust Text-to-SQL Parsing","created":"2022-10-23","cited_by_count":7,"area":null},{"id":"2310.15075","title":"TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering","created":"2023-10-23","cited_by_count":7,"area":null},{"id":"2505.18744","title":"LogicCat: A Chain-of-Thought Text-to-SQL Benchmark for Complex Reasoning","created":"2025-05-24","cited_by_count":7,"area":"lr"},{"id":"2409.15985","title":"DataGpt-SQL-7B: An Open-Source Language Model for Text-to-SQL","created":"2024-09-24","cited_by_count":5,"area":null},{"id":"2505.23838","title":"Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunities","created":"2025-05-28","cited_by_count":4,"area":null},{"id":"2506.07423","title":"SEED: Enhancing Text-to-SQL Performance and Practical Usability Through Automatic Evidence Generation","created":"2025-06-09","cited_by_count":4,"area":null},{"id":"2211.15363","title":"On the Security Vulnerabilities of Text-to-SQL Models","created":"2022-11-28","cited_by_count":3,"area":null},{"id":"2312.02251","title":"Fine-Tuning Language Models for Context-Specific SQL Query Generation","created":"2023-12-04","cited_by_count":3,"area":null},{"id":"2406.16349","title":"AnnotatedTables: A Large Tabular Dataset with Language Model Annotations","created":"2024-06-24","cited_by_count":3,"area":null},{"id":"2410.01869","title":"Enhancing LLM Fine-tuning for Text-to-SQLs by SQL Quality Measurement","created":"2024-10-02","cited_by_count":3,"area":null},{"id":"2410.22925","title":"BIS: NL2SQL Service Evaluation Benchmark for Business Intelligence Scenarios","created":"2024-10-30","cited_by_count":3,"area":null},{"id":"2509.23459","title":"MaskSQL: Safeguarding Privacy for LLM-Based Text-to-SQL via Abstraction","created":"2025-09-27","cited_by_count":3,"area":null},{"id":"2209.07258","title":"Graph-to-Text Generation with Dynamic Structure Pruning","created":"2022-09-15","cited_by_count":2,"area":null},{"id":"2307.04096","title":"Optimal Transport Posterior Alignment for Cross-lingual Semantic Parsing","created":"2023-07-09","cited_by_count":2,"area":null},{"id":"2406.03753","title":"VisTR: Visualizations as Representations for Time-series Table Reasoning","created":"2024-06-06","cited_by_count":2,"area":"lr"},{"id":"2412.05850","title":"Cooperative SQL Generation for Segmented Databases By Using Multi-functional LLM Agents","created":"2024-12-08","cited_by_count":2,"area":"agents"},{"id":"2508.06387","title":"End-to-End Text-to-SQL with Dataset Selection: Leveraging LLMs for Adaptive Query Generation","created":"2025-08-08","cited_by_count":2,"area":null},{"id":"2510.26495","title":"Rethinking Text-to-SQL: Dynamic Multi-turn SQL Interaction for Real-world Database Exploration","created":"2025-10-30","cited_by_count":2,"area":"lr"},{"id":"2307.07255","title":"Dialogue Agents 101: A Beginner's Guide to Critical Ingredients for Designing Effective Conversational Systems","created":"2023-07-14","cited_by_count":1,"area":"agents"},{"id":"2601.18012","title":"Evaluating Semantic and Syntactic Understanding in Large Language Models for Payroll Systems","created":"2026-01-25","cited_by_count":1,"area":null},{"id":"2605.10318","title":"Extending Confidence-Based Text2Cypher with Grammar and Schema Aware Filtering","created":"2026-05-11","cited_by_count":1,"area":null},{"id":"2609.08950","title":"SQLMorph: Query Mutation and Fine-Grained Metrics for Text-to-SQL Evaluation","created":"2026-09-08","cited_by_count":1,"area":null},{"id":"2302.11054","title":"Conversational Text-to-SQL: An Odyssey into State-of-the-Art and Challenges Ahead","created":"2023-02-21","cited_by_count":0,"area":null},{"id":"2508.02045","title":"Harnessing Temporal Databases for Systematic Evaluation of Factual Time-Sensitive Question-Answering in Large Language Models","created":"2025-08-04","cited_by_count":0,"area":null},{"id":"2511.08392","title":"PCRLLM: Proof-Carrying Reasoning with Large Language Models under Stepwise Logical Constraints","created":"2025-11-11","cited_by_count":0,"area":"lr"},{"id":"2511.20677","title":"Prompt Engineering Techniques for Context-dependent Text-to-SQL in Arabic","created":"2025-11-16","cited_by_count":0,"area":null},{"id":"2512.21877","title":"CricBench: A Multilingual Benchmark for Evaluating LLMs in Cricket Analytics","created":"2025-12-26","cited_by_count":0,"area":null},{"id":"2602.17001","title":"Sonar-TS: Search-Then-Verify Natural Language Querying for Time Series Databases","created":"2026-02-19","cited_by_count":0,"area":null},{"id":"2607.22624","title":"CHS-SQL: A Text-to-SQL approach based on Confidence-Guided Heuristic Search Schema Linking process","created":"2026-06-17","cited_by_count":0,"area":null},{"id":"2609.11708","title":"Language-Augmented Semantic Priors for B-Spline Surface Fitting","created":"2026-09-10","cited_by_count":0,"area":null},{"id":"2609.22917","title":"An Iterative LangGraph Agent for Text-to-SQL: Natural Language Access to the Chicago Crime Database","created":"2026-09-19","cited_by_count":0,"area":null},{"id":"2610.14777","title":"LYNX: Analytical Program Synthesis via Grounding and Closed-Loop Refinement","created":"2026-10-10","cited_by_count":0,"area":null}],"next_cursor":null}