CodexDB: Synthesizing Code for Query Processing from Natural Language Instructions using GPT-3 Codex
Summary: CodexDB leverages GPT-3 Codex to synthesize query-processing code from natural-language instructions. Decomposing complex SQL into stepwise, NL-described processing stages augmented by user guidance and database properties; prototype attains 81% WikiSQL and 62% SPIDER. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
Incoming Citations (Sorted by Pagerank)
Showing 12 of 12 citing papers.
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1 | Access Path Selection in a Relational Database Management System | 1979 | SIGMOD | 0.0040449103 |
| 71 | How Good Are Query Optimizers, Really? | 2016 | VLDB | 0.00059038975 |
| 102 | The Case for Learned Index Structures | 2018 | SIGMOD | 0.00049545203 |
| 204 | Learned Cardinalities: Estimating Correlated Joins with Deep Learning | 2019 | CIDR | 0.00034784455 |
| 333 | Neo: A Learned Query Optimizer | 2019 | VLDB | 0.00027206884 |
| 535 | ATHENA: An Ontology-Driven System for Natural Language Querying over Relational Data Stores | 2016 | VLDB | 0.00020727678 |
| 567 | NaLIR: An Interactive Natural Language Interface for Querying Relational Databases | 2014 | SIGMOD | 0.00019966681 |
| 2,349 | RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation | 2021 | VLDB | 8.9876423e-05 |
| 3,942 | Ember: No-Code Context Enrichment via Similarity-Based Keyless Joins | 2022 | VLDB | 6.6114622e-05 |
Previous
Page 1 / 1
Next