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LearnedSQLGen: Constraint-aware SQL Generation using Reinforcement Learning
Summary: Constraint-aware SQL generation via RL: LearnedSQLGen steers query synthesis toward constraint satisfaction using exploration–exploitation and execution feedback. Finite-state machine enforces valid SQL; benchmarks show ~30% accuracy gain and 10–35× speedups.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6467
- Venue
- SIGMOD
- Year
- 2022
- Pagerank
- 5.5790771e-05
- Overall Rank
- 5,289 | 63.25%
- DOI
-
10.1145/3514221.3526155
Incoming Non-self Citations Over Time
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Showing 11 of 11 citing papers.
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| 3,729 |
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| 8,636 |
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2023 |
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4.4758336e-05 |
| 8,896 |
SQL-Factory: A Multi-Agent Framework for High-Quality and Large-Scale SQL Generation |
2026 |
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A Learned Query Rewrite System |
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4.2539423e-05 |
| 10,156 |
Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload |
2026 |
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4.1905499e-05 |
| 10,212 |
SQLBarber: A System Leveraging Large Language Models to Generate Customized and Realistic SQL Workloads |
2026 |
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4.1905499e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 27 of 27 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Cited Paper |
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| 293 |
Deep Learning for Entity Matching: A Design Space Exploration |
2018 |
SIGMOD |
0.00028661817 |
| 405 |
Massive Stochastic Testing of SQL |
1998 |
VLDB |
0.00024046204 |
| 510 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00021420477 |
| 779 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00016719473 |
| 819 |
ALEX: An Updatable Adaptive Learned Index |
2020 |
SIGMOD |
0.00016237497 |
| 1,017 |
Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques |
2012 |
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0.00014627121 |
| 1,464 |
Learning Multi-dimensional Indexes |
2020 |
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0.0001184772 |
| 1,638 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00011050093 |
| 1,816 |
An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems |
2021 |
VLDB |
0.00010438512 |
| 2,280 |
Generating Targeted Queries for Database Testing |
2008 |
SIGMOD |
9.1247368e-05 |
| 2,606 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
8.4621503e-05 |
| 2,937 |
DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems |
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VLDB |
7.8552033e-05 |
| 3,241 |
A Learned Query Rewrite System using Monte Carlo Tree Search |
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VLDB |
7.32744e-05 |
| 3,411 |
SQLCheck: Automated Detection and Diagnosis of SQL Anti-Patterns |
2020 |
SIGMOD |
7.1215953e-05 |
| 3,466 |
AI Meets Database: AI4DB and DB4AI |
2021 |
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7.0645718e-05 |
| 3,580 |
Query Performance Prediction for Concurrent Queries using Graph Embedding |
2020 |
VLDB |
6.9460425e-05 |
| 3,750 |
DIAMetrics: Benchmarking Query Engines at Scale |
2020 |
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6.7864305e-05 |
| 4,543 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
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6.0953507e-05 |
| 4,587 |
MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems |
2021 |
SIGMOD |
6.0594195e-05 |
| 4,621 |
Automated Generation of Materialized Views in Oracle |
2020 |
VLDB |
6.036749e-05 |
| 4,640 |
A genetic approach for random testing of database systems |
2007 |
VLDB |
6.0226611e-05 |
| 5,386 |
Selective Data Acquisition in the Wild for Model Charging |
2022 |
VLDB |
5.5346315e-05 |
| 5,787 |
Machine Learning for Databases |
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| 5,799 |
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5.3219666e-05 |
| 5,815 |
Database Benchmarking for Supporting Real-Time Interactive Querying of Large Data |
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SIGMOD |
5.3158788e-05 |
| 7,308 |
DBMind: A Self-Driving Platform in openGauss |
2021 |
VLDB |
4.7620018e-05 |
| 7,580 |
Human-in-the-loop Outlier Detection |
2020 |
SIGMOD |
4.7023767e-05 |
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