Text-To-SQL on SParC

Metric: question match accuracy (higher is better)

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#	Model↕	question match accuracy▼	Extra Data	Paper	Date↕	Code
1	RASAT+PICARD	67.7	No	RASAT: Integrating Relational Structures into Pr...	2022-05-14	Code
2	RAT-SQL-TC + GAP	65.7	No	Pay More Attention to History: A Context Modelli...	2021-12-16	Code
3	HIE-SQL + GraPPa	64.6	No	-	-	-
4	RAT-SQL + SCoRe	62.4	No	-	-	-
5	EditSQL + BERT	47.9	No	Editing-Based SQL Query Generation for Cross-Dom...	2019-09-02	Code
6	GAZP + BERT	45.9	No	Grounded Adaptation for Zero-shot Executable Sem...	2020-09-16	Code
7	SyntaxSQL-con	20.2	No	SyntaxSQLNet: Syntax Tree Networks for Complex a...	2018-10-11	Code

#1RASAT+PICARDSOTA
67.7
question match accuracy· 2022-05-14
RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL Code
#2RAT-SQL-TC + GAPSOTA
65.7
question match accuracy· 2021-12-16
Pay More Attention to History: A Context Modelling Strategy for Conversational Text-to-SQL Code
#3HIE-SQL + GraPPa
64.6
question match accuracy
No paper
#4RAT-SQL + SCoRe
62.4
question match accuracy
No paper
#5EditSQL + BERTSOTA
47.9
question match accuracy· 2019-09-02
Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions Code
#6GAZP + BERT
45.9
question match accuracy· 2020-09-16
Grounded Adaptation for Zero-shot Executable Semantic Parsing Code
#7SyntaxSQL-conSOTA
20.2
question match accuracy· 2018-10-11
SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task Code