Text to SQL
193 papers with code • 1 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Text to SQL
Trend | Dataset | Best Model | Paper | Code | Compare |
---|
Libraries
Use these libraries to find Text to SQL models and implementationsMost implemented papers
Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task
We define a new complex and cross-domain semantic parsing and text-to-SQL task where different complex SQL queries and databases appear in train and test sets.
Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation
We present a neural approach called IRNet for complex and cross-domain Text-to-SQL.
Content Enhanced BERT-based Text-to-SQL Generation
We present a simple methods to leverage the table content for the BERT-based model to solve the text-to-SQL problem.
A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL
On the other hand, we implement the ICL approach with an example selection method based on named entity recognition to prevent overemphasis on entities.
SParC: Cross-Domain Semantic Parsing in Context
The best model obtains an exact match accuracy of 20. 2% over all questions and less than10% over all interaction sequences, indicating that the cross-domain setting and the con-textual phenomena of the dataset present significant challenges for future research.
RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers
The generalization challenge lies in (a) encoding the database relations in an accessible way for the semantic parser, and (b) modeling alignment between database columns and their mentions in a given query.
Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions
We focus on the cross-domain context-dependent text-to-SQL generation task.
CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases
We present CoSQL, a corpus for building cross-domain, general-purpose database (DB) querying dialogue systems.
Semantic Evaluation for Text-to-SQL with Distilled Test Suites
We propose test suite accuracy to approximate semantic accuracy for Text-to-SQL models.
Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training
Most recently, there has been significant interest in learning contextual representations for various NLP tasks, by leveraging large scale text corpora to train large neural language models with self-supervised learning objectives, such as Masked Language Model (MLM).