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SQL Parsing

Papers

Showing 125 of 50 papers

TitleStatusHype
RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQLCode2
When is Tree Search Useful for LLM Planning? It Depends on the DiscriminatorCode2
MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQLCode2
EHR-SeqSQL : A Sequential Text-to-SQL Dataset For Interactively Exploring Electronic Health RecordsCode1
Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLsCode1
Learning to Synthesize Data for Semantic ParsingCode1
Optimizing Deeper Transformers on Small DatasetsCode1
Semantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking GraphCode1
SQLFixAgent: Towards Semantic-Accurate Text-to-SQL Parsing via Consistency-Enhanced Multi-Agent CollaborationCode1
Text-to-SQL Error Correction with Language Models of CodeCode1
Weakly Supervised Text-to-SQL Parsing through Question DecompositionCode1
A Tale of Two Linkings: Dynamically Gating between Schema Linking and Structural Linking for Text-to-SQL ParsingCode0
Towards Generalizable and Robust Text-to-SQL ParsingCode0
Global Reasoning over Database Structures for Text-to-SQL ParsingCode0
STAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL ParsingCode0
SUN: Exploring Intrinsic Uncertainties in Text-to-SQL ParsersCode0
SynTQA: Synergistic Table-based Question Answering via Mixture of Text-to-SQL and E2E TQACode0
Proton: Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL ParsingCode0
Improving Text-to-SQL Evaluation MethodologyCode0
Representing Schema Structure with Graph Neural Networks for Text-to-SQL ParsingCode0
Semantic Decomposition of Question and SQL for Text-to-SQL ParsingCode0
Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL ParsingCode0
Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL ParsingCode0
KaggleDBQA: Realistic Evaluation of Text-to-SQL ParsersCode0
Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsing0
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