{"total":111,"rows":[{"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":"2411.07763","title":"Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows","created":"2024-11-12","cited_by_count":232,"area":null},{"id":"2405.16755","title":"CHESS: Contextual Harnessing for Efficient SQL Synthesis","created":"2024-05-27","cited_by_count":169,"area":null},{"id":"2402.17944","title":"Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey","created":"2024-02-27","cited_by_count":159,"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":"2405.07467","title":"MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generation","created":"2024-05-13","cited_by_count":105,"area":null},{"id":"2403.19318","title":"TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios","created":"2024-03-28","cited_by_count":77,"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":"2408.05109","title":"A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?","created":"2024-08-09","cited_by_count":56,"area":null},{"id":"2502.14913","title":"OpenSearch-SQL: Enhancing Text-to-SQL with Dynamic Few-shot and Consistency Alignment","created":"2025-02-19","cited_by_count":53,"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":"2405.15307","title":"Before Generation, Align it! A Novel and Effective Strategy for Mitigating Hallucinations in Text-to-SQL Generation","created":"2024-05-24","cited_by_count":50,"area":null},{"id":"2402.01117","title":"DTS-SQL: Decomposed Text-to-SQL with Small Large Language Models","created":"2024-02-02","cited_by_count":45,"area":null},{"id":"2507.04701","title":"XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL","created":"2025-07-07","cited_by_count":40,"area":null},{"id":"2401.10506","title":"FinSQL: Model-Agnostic LLMs-based Text-to-SQL Framework for Financial Analysis","created":"2024-01-19","cited_by_count":36,"area":null},{"id":"2402.11517","title":"Knowledge-to-SQL: Enhancing SQL Generation with Data Expert LLM","created":"2024-02-18","cited_by_count":35,"area":null},{"id":"2406.12692","title":"MAGIC: Generating Self-Correction Guideline for In-Context Text-to-SQL","created":"2024-06-18","cited_by_count":35,"area":null},{"id":"2406.19073","title":"AMBROSIA: A Benchmark for Parsing Ambiguous Questions into Database Queries","created":"2024-06-27","cited_by_count":35,"area":null},{"id":"2409.16751","title":"E-SQL: Direct Schema Linking via Question Enrichment in Text-to-SQL","created":"2024-09-25","cited_by_count":35,"area":null},{"id":"2403.20014","title":"PURPLE: Making a Large Language Model a Better SQL Writer","created":"2024-03-29","cited_by_count":34,"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":"2501.12372","title":"Is Long Context All You Need? Leveraging LLM's Extended Context for NL2SQL","created":"2025-01-21","cited_by_count":30,"area":null},{"id":"2503.18596","title":"LinkAlign: Scalable Schema Linking for Real-World Large-Scale Multi-Database Text-to-SQL","created":"2025-03-24","cited_by_count":29,"area":null},{"id":"2310.17894","title":"Natural Language Interfaces for Tabular Data Querying and Visualization: A Survey","created":"2023-10-27","cited_by_count":27,"area":null},{"id":"2403.09732","title":"PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency","created":"2024-03-13","cited_by_count":27,"area":null},{"id":"2410.12916","title":"MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation","created":"2024-10-16","cited_by_count":19,"area":null},{"id":"2511.17190","title":"AutoLink: Autonomous Schema Exploration and Expansion for Scalable Schema Linking in Text-to-SQL at Scale","created":"2025-11-21","cited_by_count":17,"area":null},{"id":"2503.07871","title":"MapQA: Open-domain Geospatial Question Answering on Map Data","created":"2025-03-10","cited_by_count":15,"area":null},{"id":"2501.09310","title":"Understanding, Detecting, and Repairing Real-World In-Context-Learning-Based Text-to-SQL Errors","created":"2025-01-16","cited_by_count":14,"area":null},{"id":"2412.10138","title":"ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQL","created":"2024-12-13","cited_by_count":13,"area":null},{"id":"2402.08349","title":"Evaluating the Data Model Robustness of Text-to-SQL Systems Based on Real User Queries","created":"2024-02-13","cited_by_count":12,"area":null},{"id":"2405.09593","title":"SQL-to-Schema Enhances Schema Linking in Text-to-SQL","created":"2024-05-15","cited_by_count":12,"area":null},{"id":"2409.19014","title":"FLEX: Expert-level False-Less EXecution Metric for Reliable Text-to-SQL Benchmark","created":"2024-09-24","cited_by_count":11,"area":null},{"id":"2412.12522","title":"Solid-SQL: Enhanced Schema-linking based In-context Learning for Robust Text-to-SQL","created":"2024-12-17","cited_by_count":11,"area":null},{"id":"2511.10192","title":"Text2SQL-Flow: A Robust SQL-Aware Data Augmentation Framework for Text-to-SQL","created":"2025-11-13","cited_by_count":11,"area":null},{"id":"2312.10321","title":"LLM-SQL-Solver: Can LLMs Determine SQL Equivalence?","created":"2023-12-16","cited_by_count":10,"area":null},{"id":"2507.22478","title":"SLM-SQL: An Exploration of Small Language Models for Text-to-SQL","created":"2025-07-30","cited_by_count":10,"area":null},{"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":"2505.22096","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","created":"2025-05-28","cited_by_count":9,"area":null},{"id":"2404.14453","title":"EPI-SQL: Enhancing Text-to-SQL Translation with Error-Prevention Instructions","created":"2024-04-21","cited_by_count":8,"area":null},{"id":"2411.02948","title":"Grounding Natural Language to SQL Translation with Data-Based Self-Explanations","created":"2024-11-05","cited_by_count":8,"area":null},{"id":"2504.02327","title":"LearNAT: Learning NL2SQL with AST-guided Task Decomposition for Large Language Models","created":"2025-04-03","cited_by_count":8,"area":null},{"id":"2311.01862","title":"$R^3$-NL2GQL: A Model Coordination and Knowledge Graph Alignment Approach for NL2GQL","created":"2023-11-03","cited_by_count":7,"area":null},{"id":"2407.14568","title":"SQLfuse: Enhancing Text-to-SQL Performance through Comprehensive LLM Synergy","created":"2024-07-19","cited_by_count":7,"area":null},{"id":"2510.23854","title":"Can LLMs Narrate Tabular Data? An Evaluation Framework for Natural Language Representations of Text-to-SQL System Outputs","created":"2025-10-27","cited_by_count":7,"area":null},{"id":"2406.14545","title":"Unmasking Database Vulnerabilities: Zero-Knowledge Schema Inference Attacks in Text-to-SQL Systems","created":"2024-06-20","cited_by_count":6,"area":null},{"id":"2405.06674","title":"Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models","created":"2024-05-04","cited_by_count":5,"area":null},{"id":"2403.00872","title":"DFIN-SQL: Integrating Focused Schema with DIN-SQL for Superior Accuracy in Large-Scale Databases","created":"2024-03-01","cited_by_count":4,"area":null},{"id":"2502.11438","title":"SAFE-SQL: Self-Augmented In-Context Learning with Fine-grained Example Selection for Text-to-SQL","created":"2025-02-17","cited_by_count":4,"area":null},{"id":"2503.21602","title":"GenEdit: Compounding Operators and Continuous Improvement to Tackle Text-to-SQL in the Enterprise","created":"2025-03-27","cited_by_count":4,"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":"2510.14296","title":"Rethinking Schema Linking: A Context-Aware Bidirectional Retrieval Approach for Text-to-SQL","created":"2025-10-16","cited_by_count":4,"area":null},{"id":"2406.00014","title":"KU-DMIS at EHRSQL 2024:Generating SQL query via question templatization in EHR","created":"2024-05-22","cited_by_count":3,"area":null},{"id":"2407.07313","title":"ETM: Modern Insights into Perspective on Text-to-SQL Evaluation in the Age of Large Language Models","created":"2024-07-10","cited_by_count":3,"area":null},{"id":"2502.11022","title":"MultiTEND: A Multilingual Benchmark for Natural Language to NoSQL Query Translation","created":"2025-02-16","cited_by_count":3,"area":null},{"id":"2503.13342","title":"Valid Text-to-SQL Generation with Unification-based DeepStochLog","created":"2025-03-17","cited_by_count":3,"area":null},{"id":"2506.00912","title":"Pi-SQL: Enhancing Text-to-SQL with Fine-Grained Guidance from Pivot Programming Languages","created":"2025-06-01","cited_by_count":3,"area":null},{"id":"2508.14056","title":"Confidence Estimation for Text-to-SQL in Large Language Models","created":"2025-08-08","cited_by_count":3,"area":null},{"id":"2604.25149","title":"Semantic Layers for Reliable LLM-Powered Data Analytics: A Paired Benchmark of Accuracy and Hallucination Across Three Frontier Models","created":"2026-04-28","cited_by_count":3,"area":null},{"id":"2401.12379","title":"Analyzing the Effectiveness of Large Language Models on Text-to-SQL Synthesis","created":"2024-01-22","cited_by_count":2,"area":null},{"id":"2405.08839","title":"PromptMind Team at EHRSQL-2024: Improving Reliability of SQL Generation using Ensemble LLMs","created":"2024-05-14","cited_by_count":2,"area":null},{"id":"2410.09174","title":"Context-Aware SQL Error Correction Using Few-Shot Learning -- A Novel Approach Based on NLQ, Error, and SQL Similarity","created":"2024-10-11","cited_by_count":2,"area":null},{"id":"2412.07214","title":"Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models","created":"2024-12-10","cited_by_count":2,"area":null},{"id":"2503.17811","title":"Feather-SQL: A Lightweight NL2SQL Framework with Dual-Model Collaboration Paradigm for Small Language Models","created":"2025-03-22","cited_by_count":2,"area":null},{"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":"2510.01989","title":"Exploring Database Normalization Effects on SQL Generation","created":"2025-10-02","cited_by_count":2,"area":null},{"id":"2603.03742","title":"ErrorLLM: Modeling SQL Errors for Text-to-SQL Refinement","created":"2026-03-04","cited_by_count":2,"area":null},{"id":"2606.31041","title":"A Semantic-Layer-Mediated Agent for Natural Language to SQL over Heterogeneous Enterprise Databases","created":"2026-06-30","cited_by_count":2,"area":null},{"id":"2308.11891","title":"Bridging the Gap: Deciphering Tabular Data Using Large Language Model","created":"2023-08-23","cited_by_count":1,"area":null},{"id":"2402.13740","title":"From Text to CQL: Bridging Natural Language and Corpus Search Engine","created":"2024-02-21","cited_by_count":1,"area":null},{"id":"2406.14313","title":"Iterative Repair with Weak Verifiers for Few-shot Transfer in KBQA with Unanswerability","created":"2024-06-20","cited_by_count":1,"area":null},{"id":"2406.17574","title":"Beyond Text-to-SQL for IoT Defense: A Comprehensive Framework for Querying and Classifying IoT Threats","created":"2024-06-25","cited_by_count":1,"area":null},{"id":"2407.12749","title":"ChipXplore: Natural Language Exploration of Hardware Designs and Libraries","created":"2024-07-17","cited_by_count":1,"area":null},{"id":"2407.15071","title":"Relational Database Augmented Large Language Model","created":"2024-07-21","cited_by_count":1,"area":null},{"id":"2410.22082","title":"An Actor-Critic Approach to Boosting Text-to-SQL Large Language Model","created":"2024-10-28","cited_by_count":1,"area":null},{"id":"2504.16358","title":"Text-to-TrajVis: Enabling Trajectory Data Visualizations from Natural Language Questions","created":"2025-04-23","cited_by_count":1,"area":null},{"id":"2506.11986","title":"Schema-R1: A reasoning training approach for schema linking in Text-to-SQL Task","created":"2025-06-13","cited_by_count":1,"area":null},{"id":"2511.00985","title":"ORANGE: An Online Reflection ANd GEneration framework with Domain Knowledge for Text-to-SQL","created":"2025-11-02","cited_by_count":1,"area":null},{"id":"2512.16083","title":"Scaling Text2SQL via LLM-efficient Schema Filtering with Functional Dependency Graph Rerankers","created":"2025-12-18","cited_by_count":1,"area":null},{"id":"2602.15564","title":"Beyond Static Pipelines: Learning Dynamic Workflows for Text-to-SQL","created":"2026-02-17","cited_by_count":1,"area":null},{"id":"2604.16493","title":"NL2SQLBench: A Modular Benchmarking Framework for LLM-Enabled NL2SQL Solutions","created":"2026-04-13","cited_by_count":1,"area":null},{"id":"2605.00628","title":"EGREFINE: An Execution-Grounded Optimization Framework for Text-to-SQL Schema Refinement","created":"2026-05-01","cited_by_count":1,"area":null},{"id":"2605.29670","title":"EviLink: Multi-Path Schema Linking with Uncertainty-Guided Evidence Acquisition for Large-Scale Text-to-SQL","created":"2026-05-28","cited_by_count":1,"area":null},{"id":"2606.23537","title":"SQLConductor: Search-to-Policy Learning for Step-wise Text-to-SQL Orchestration","created":"2026-06-22","cited_by_count":1,"area":null},{"id":"2410.11457","title":"LR-SQL: A Supervised Fine-Tuning Method for Text2SQL Tasks under Low-Resource Scenarios","created":"2024-10-15","cited_by_count":0,"area":null},{"id":"2503.07996","title":"SQLCritic: Correcting Text-to-SQL Generation via Clause-wise Critic","created":"2025-03-11","cited_by_count":0,"area":null},{"id":"2505.18122","title":"UNJOIN: Enhancing Multi-Table Text-to-SQL Generation via Schema Simplification","created":"2025-05-23","cited_by_count":0,"area":null},{"id":"2505.20591","title":"Effectiveness of Prompt Optimization in NL2SQL Systems","created":"2025-05-26","cited_by_count":0,"area":null},{"id":"2506.03598","title":"Auto prompt sql: a resource-efficient architecture for text-to-sql translation in constrained environments","created":"2025-06-04","cited_by_count":0,"area":null},{"id":"2509.05899","title":"X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs","created":"2025-09-07","cited_by_count":0,"area":null},{"id":"2509.09684","title":"Text-to-SQL Oriented to the Process Mining Domain: A PT-EN Dataset for Query Translation","created":"2025-08-18","cited_by_count":0,"area":null},{"id":"2509.19371","title":"How to inject knowledge efficiently? Knowledge Infusion Scaling Law for Pre-training Large Language Models","created":"2025-09-19","cited_by_count":0,"area":null},{"id":"2511.18934","title":"Skeletons Matter: Dynamic Data Augmentation for Text-to-Query","created":"2025-11-24","cited_by_count":0,"area":null},{"id":"2603.05996","title":"Track-SQL: Enhancing Generative Language Models with Dual-Extractive Modules for Schema and Context Tracking in Multi-turn Text-to-SQL","created":"2026-03-06","cited_by_count":0,"area":null},{"id":"2604.12988","title":"ROSE: An Intent-Centered Evaluation Metric for NL2SQL","created":"2026-04-14","cited_by_count":0,"area":null},{"id":"2604.16511","title":"SQL Query Engine: A Self-Healing LLM Pipeline for Natural Language to PostgreSQL Translation","created":"2026-04-15","cited_by_count":0,"area":null},{"id":"2605.21792","title":"Residual Skill Optimization for Text-to-SQL Ensembles","created":"2026-05-20","cited_by_count":0,"area":null},{"id":"2606.05906","title":"ACE-SQL: Adaptive Co-Optimization via Empirical Credit Assignment for Text-to-SQL","created":"2026-06-04","cited_by_count":0,"area":null},{"id":"2606.08245","title":"ZAS-SQL: Distilling Rules from Failures for Zero-Shot Text-to-SQL","created":"2026-06-06","cited_by_count":0,"area":null}],"next_cursor":"100"}