SOTAVerified

Text-To-SQL

Text-to-SQL is a task in natural language processing (NLP) where the goal is to automatically generate SQL queries from natural language text. The task involves converting the text input into a structured representation and then using this representation to generate a semantically correct SQL query that can be executed on a database.

( Image credit: SyntaxSQLNet )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 301–350 of 424 papers

TitleStatusHype
Schema-Aware Multi-Task Learning for Complex Text-to-SQL—0
SchemaGraphSQL: Efficient Schema Linking with Pathfinding Graph Algorithms for Text-to-SQL on Large-Scale Databases—0
Controllable Data Augmentation for Context-Dependent Text-to-SQL—0
SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing—0
SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes—0
Contrato360 2.0: A Document and Database-Driven Question-Answer System using Large Language Models and Agents—0
SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoising—0
CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation—0
A Benchmark to Understand the Role of Knowledge Graphs on Large Language Model's Accuracy for Question Answering on Enterprise SQL Databases—0
Archer: A Human-Labeled Text-to-SQL Dataset with Arithmetic, Commonsense and Hypothetical Reasoning—0
Self-supervised Text-to-SQL Learning with Header Alignment Training—0
An Actor-Critic Approach to Boosting Text-to-SQL Large Language Model—0
CoddLLM: Empowering Large Language Models for Data Analytics—0
Cheaper, Better, Faster, Stronger: Robust Text-to-SQL without Chain-of-Thought or Fine-Tuning—0
Semantic Evaluation for Text-to-SQL with Distilled Test Suite—0
Semantic Parsing for Complex Data Retrieval: Targeting Query Plans vs. SQL for No-Code Access to Relational Databases—0
UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQL—0
CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL—0
Chase: A Large-Scale and Pragmatic Chinese Dataset for Cross-Database Context-Dependent Text-to-SQL—0
Service-oriented Text-to-SQL Parsing—0
SeSQL: Yet Another Large-scale Session-level Chinese Text-to-SQL Dataset—0
UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQL—0
SHARE: An SLM-based Hierarchical Action CorREction Assistant for Text-to-SQL—0
Ambiguity Resolution in Text-to-Structured Data Mapping—0
Solid-SQL: Enhanced Schema-linking based In-context Learning for Robust Text-to-SQL—0
UNJOIN: Enhancing Multi-Table Text-to-SQL Generation via Schema Simplification—0
Sparks of Tabular Reasoning via Text2SQL Reinforcement Learning—0
CEGI: Measuring the trade-off between efficiency and carbon emissions for SLMs and VLMs—0
CCoE: A Compact LLM with Collaboration of Experts—0
Speak to your Parser: Interactive Text-to-SQL with Natural Language Feedback—0
Speech-to-SQL Parsing: Error Correction with Multi-modal Representations—0
Speech-to-SQL: Towards Speech-driven SQL Query Generation From Natural Language Question—0
Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows—0
Calibrating LLMs for Text-to-SQL Parsing by Leveraging Sub-clause Frequencies—0
SPSQL: Step-by-step Parsing Based Framework for Text-to-SQL Generation—0
R^3: "This is My SQL, Are You With Me?" A Consensus-Based Multi-Agent System for Text-to-SQL Tasks—0
SQLCritic: Correcting Text-to-SQL Generation via Clause-wise Critic—0
SQLens: An End-to-End Framework for Error Detection and Correction in Text-to-SQL—0
Bridging the Generalization Gap in Text-to-SQL Parsing with Schema Expansion—0
SQLForge: Synthesizing Reliable and Diverse Data to Enhance Text-to-SQL Reasoning in LLMs—0
Addressing Limitations of Encoder-Decoder Based Approach to Text-to-SQL—0
SQLfuse: Enhancing Text-to-SQL Performance through Comprehensive LLM Synergy—0
SQL-GEN: Bridging the Dialect Gap for Text-to-SQL Via Synthetic Data And Model Merging—0
Unmasking Database Vulnerabilities: Zero-Knowledge Schema Inference Attacks in Text-to-SQL Systems—0
Bridging the Gap: Transforming Natural Language Questions into SQL Queries via Abstract Query Pattern and Contextual Schema Markup—0
Beyond Text-to-SQL for IoT Defense: A Comprehensive Framework for Querying and Classifying IoT Threats—0
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)—0
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data—0
SQL-to-Schema Enhances Schema Linking in Text-to-SQL—0
STAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL Parsing—0
Show:102550
← PrevPage 7 of 9Next →
All datasetsBIRD (BIg Bench for LaRge-scale Database Grounded Text-to-SQL Evaluation)spiderSpider 2.0SParCKaggleDBQASEDESQL-EvalText-To-SQL

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Human PerformanceExecution Accurarcy (Human)92.96—Unverified
2XiYan-SQLExecution Accuracy % (Test)75.63—Unverified
3DSAIR + GPT-4oExecution Accuracy % (Test)74.12—Unverified
4CHASE-SQL + GeminiExecution Accuracy % (Test)74.06—Unverified
5ExSL + granite-34b-codeExecution Accuracy % (Test)73.17—Unverified
6OpenSearch-SQL+ v2 + GPT-4oExecution Accuracy % (Test)72.28—Unverified
7Distillery + GPT-4oExecution Accuracy % (Test)71.83—Unverified
8Insights AIExecution Accuracy % (Test)70.26—Unverified
9PURPLE + RED + GPT-4oExecution Accuracy % (Test)70.21—Unverified
10MCTS-SQLExecution Accuracy % (Test)69.4—Unverified
#ModelMetricClaimedVerifiedStatus
1XiYan-SQLExecution Accuracy (Test)89.65—Unverified
2PET-SQLExecution Accuracy (Test)87.6—Unverified
3datagpt-sql-7B + InvalidSQL-FeedbackExecution Accuracy (Dev)87.2—Unverified
4DAIL-SQL + GPT-4 + Self-ConsistencyExecution Accuracy (Test)86.6—Unverified
5DIN-SQL + GPT-4Execution Accuracy (Test)85.3—Unverified
6datagpt-sql-7BExecution Accuracy (Dev)84.8—Unverified
7MSc-SQLExecution Accuracy (Test)84.7—Unverified
8MARLO + Claude 2.1Execution Accuracy (Test)84—Unverified
9C3 + ChatGPT + Zero-ShotExecution Accuracy (Test)82.3—Unverified
10code-davinci-002 175B (LEVER)Execution Accuracy (Dev)81.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Spider-Agent + o1-previewSuccess Rate17.03—Unverified
2Spider-Agent + GPT-4oSuccess Rate10.13—Unverified
3Spider-Agent + Claude-3.5-SonnectSuccess Rate9.02—Unverified
4Spider-Agent + GPT-4Success Rate8.86—Unverified
5Spider-Agent + Qwen2.5-72BSuccess Rate6.17—Unverified
6Spider-Agent + DeepSeek-V2.5Success Rate5.22—Unverified
7Spider-Agent + Gemini-Pro-1.5Success Rate2.53—Unverified
8Spider-Agent + Llama-3.1-405BSuccess Rate2.21—Unverified
#ModelMetricClaimedVerifiedStatus
1RASAT+PICARDinteraction match accuracy45.2—Unverified
2RAT-SQL-TC + GAPinteraction match accuracy43.2—Unverified
3HIE-SQL + GraPPainteraction match accuracy42.9—Unverified
4RAT-SQL + SCoReinteraction match accuracy38.1—Unverified
5EditSQL + BERTinteraction match accuracy25.3—Unverified
6GAZP + BERTinteraction match accuracy23.5—Unverified
7SyntaxSQL-coninteraction match accuracy5.2—Unverified
#ModelMetricClaimedVerifiedStatus
1RAT-SQLExact Match (EM)26.77—Unverified
2Edit-SQLExact Match (EM)11.73—Unverified
#ModelMetricClaimedVerifiedStatus
1T5-LargePCM-F1 (dev)48.2—Unverified
#ModelMetricClaimedVerifiedStatus
1XiYan-SQLExecution Accuracy69.86—Unverified
#ModelMetricClaimedVerifiedStatus
1Orange-mini0-shot MRR74.17—Unverified