Text-To-Sql
( Image credit: SyntaxSQLNet )
Leaderboards
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
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Greatest papers with code
SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning
Existing state-of-the-art approaches rely on reinforcement learning to reward the decoder when it generates any of the equivalent serializations.
SOTA for Text-To-Sql on WikiSQL
Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning
A significant amount of the world's knowledge is stored in relational databases.
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.
SOTA for Semantic Parsing on spider
Improving Text-to-SQL Evaluation Methodology
ACL 2018
• jkkummerfeld/text2sql-data
• 
Second, we show that the current division of data into training and test sets measures robustness to variations in the way questions are asked, but only partially tests how well systems generalize to new queries; therefore, we propose a complementary dataset split for evaluation of future work.
SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task
• taoyds/syntaxsql
• 
In this paper we propose SyntaxSQLNet, a syntax tree network to address the complex and cross-domain text-to-SQL generation task.
TypeSQL: Knowledge-based Type-Aware Neural Text-to-SQL Generation
Interacting with relational databases through natural language helps users of any background easily query and analyze a vast amount of data.
Robust Text-to-SQL Generation with Execution-Guided Decoding
We consider the problem of neural semantic parsing, which translates natural language questions into executable SQL queries.
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.
A Pilot Study for Chinese SQL Semantic Parsing
The task of semantic parsing is highly useful for dialogue and question answering systems.
QUESTION ANSWERING SEMANTIC PARSING TEXT-TO-SQL WORD EMBEDDINGS
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.