Curated tutorials and resources for Large Language Models, Text2SQL, and more.
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Curated tutorials and resources for Large Language Models, Text2SQL, and more.
We warmly welcome contributions from everyone, whether you've found a typo, a bug, have a suggestion, or want to share a resource related to LLM+Text2SQL. For detailed guidelines on how to contribute, please see our CONTRIBUTING.md file.
WikiSQL | Spider Exact Match(EM) |
Spider Exact Execution(EX) |
BIRD Valid Efficiency Score (VES) |
BIRD Execution Accuracy (EX) |
|
---|---|---|---|---|---|
🏆1 | 93.0 (2021/05-SeaD+Execution-Guided Decoding) |
74.0 (2022/09-Graphix-3B + PICARD) |
86.6 (2023/08-DAIL-SQL + GPT-4 + Self-Consistency) |
64.22 (2023/10-SFT CodeS-15B) |
60.37 (2023/10-SFT CodeS-15B) |
🥈2 | 92.7 (2021/03-SDSQL+Execution-Guided Decoding) |
73.9 (2022/09-CatSQL + GraPPa) |
86.2 (2023/08-DAIL-SQL + GPT-4) |
63.62 (2023/10-SFT CodeS-7B) |
59.25 (2023/10-SFT CodeS-7B) |
🥉3 | 92.5 (2020/11-IE-SQL+Execution-Guided Decoding) |
73.1 (2022/09-SHiP + PICARD) |
85.3 (2023/04-DIN-SQL + GPT-4) |
60.77 (2023/07-GPT-4) |
55.90 (2023/08-DIN-SQL + GPT-4) |
4 | 92.2 (2020/03-HydraNet+Execution-Guided Decoding) |
72.9 (2022/05-G³R + LGESQL + ELECTRA) |
83.9 (2023/07-Hindsight Chain of Thought with GPT-4) |
59.44 (2023/08-DIN-SQL + GPT-4) |
54.89 (2023/07-GPT-4) |
5 | 91.9 (2020/12-BRIDGE+Execution-Guided Decoding) |
72.4 (2022/08-RESDSQL+T5-1.1-lm100k-xl) |
82.3 (2023/06-C3 + ChatGPT + Zero-Shot) |
56.99 (2023/10-SFT CodeS-15B) |
52.15 (2023/10-SFT CodeS-15B) |
6 | 91.8 (2019/08-X-SQL+Execution-Guided Decoding) |
72.4 (2022/05-T5-SR) |
80.8 (2023/07-Hindsight Chain of Thought with GPT-4 and Instructions) |
56.56 (2023/03-ChatGPT + CoT) |
50.25 (2023/10-SFT CodeS-7B) |
7 | 91.4 (2021/03-SDSQL) |
72.2 (2022/12-N-best List Rerankers + PICARD) |
79.9 (2023/02-RESDSQL-3B + NatSQ) |
54.84 (2023/10-SFT CodeS-7B) |
49.02 (2023/07-Claude-2) |
8 | 91.1 (2020/12-BRIDGE) |
72.1 (2021/09-S²SQL + ELECTRA ) |
78.5 (2022/11-SeaD + PQL) |
51.40 (2023/03-ChatGPT) |
40.08 (2023/03-ChatGPT + CoT) |
9 | 91.0 (2021/04-Text2SQLGen + EG) |
72.0 (2023/02-RESDSQL-3B + NatSQL) |
78.2 (2023/04-DIN-SQL + CodeX) |
49.69 (2023/03-ChatGPT + CoT) |
39.30 (2023/03-ChatGPT) |
10 | 90.5 (2020/11-SeqGenSQL+EG) |
72.0 (2021/06-LGESQL + ELECTRA ) |
78.0 (2023/08-T5-3B+NatSQL+Token Preprocessing) |
41.60 (2023/02-Codex) |
36.47 (2023/02-Codex) |
(2023-arXiv, None) Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation [paper] [code]
(2023-AAAI 2023, CCF-A) RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL [paper] [code]
(2023-arXiv, None) Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs [paper] [code]
(2023-arXiv, None) DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction [paper] [code]
(2023-arXiv, None) A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability [paper] [code]
(2023-ICLR, CCF-A) Binding Language Models in Symbolic Languages [paper] [code]
(2023-SIGMOD, CCF-A) Few-shot Text-to-SQL Translation using Structure and Content Prompt Learning [paper] [code]
(2023-ICASSP, CCF-B) T5-SR: A Unified Seq-to-Seq Decoding Strategy for Semantic Parsing [paper]
(2022-ACL, CCF-A) S2SQL: Injecting Syntax to Question-Schema Interaction Graph Encoder for Text-to-SQL Parsers [paper]
(2022-NAACL, CCF-B) SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoising [paper]
(2022-EMNLP, CCF-B) STAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL Parsing [paper] [code]
(2022-EMNLP, CCF-B) RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL [paper] [code]
(2022-EMNLP, CCF-B) CQR-SQL: Conversational Question Reformulation Enhanced Context-Dependent Text-to-SQL Parsers [paper]
(2022-ACL, CCF-A) HIE-SQL: History Information Enhanced Network for Context-Dependent Text-to-SQL Semantic Parsing [paper]
(2022-arXiv, None) Importance of Synthesizing High-quality Data for Text-to-SQL Parsing [paper]
(2021-ACL, CCF-A) Decoupled Dialogue Modeling and Semantic Parsing for Multi-Turn Text-to-SQL [paper]
(2021-arXiv, None) Pay More Attention to History: A Context Modelling Strategy for Conversational Text-to-SQL [paper] [code]
(2021-ICLR, CCF-A) SCORE: Pre-training for Context Representation in Conversational Semantic Parsing [paper]
(2021-DASFAA, CCF-B) An Interactive NL2SQL Approach with Reuse Strategy [paper]
(2021-NAACL, CCF-B) Structure-Grounded Pretraining for Text-to-SQL [paper]
(2021-EMNLP, CCF-B) PICARD:Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models [paper] [code]
(2021-ICLR, CCF-A) GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing [paper] [code]
(2021-ACL, CCF-A) LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations [paper] [code]
(2020-EMNLP, CCF-B) Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing [paper] [code]
(2020-ACL, CCF-A) TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data [paper] [code]
(2020-ACL, CCF-A) RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers [paper] [code]
(2020-EMNLP, CCF-B) Mention Extraction and Linking for SQL Query Generation [paper]
(2020-EMNLP, CCF-B) IGSQL: Database Schema Interaction Graph Based Neural Model for Context-Dependent Text-to-SQL Generation [paper] [code]
(2020-arXiv, None) Hybrid Ranking Network for Text-to-SQL [paper] [code]
(2019-arXiv, None) X-SQL: reinforce schema representation with context [paper]
(2019-EMNLP, CCF-B) Global Reasoning over Database Structures for Text-to-SQL Parsing [paper] [code]
(2019-EMNLP, CCF-B) Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions [paper] [code]
(2019-ACL, CCF-A) Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing [paper] [code]
(2019-ACL, CCF-A) Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation [paper] [code]
(2018-EMNLP, CCF-B) SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task [paper] [code]
(2018-NAACL, CCF-B) TypeSQL: Knowledge-based Type-Aware Neural Text-to-SQL Generation [paper] [code]
(2017-arXiv, None) SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning [paper] [code]
ChatGLM [paper] [code] [model]
WizardLM [paper] [code] [model]
ChatGLM2[paper] [code] [model]
InternLM [paper] [code] [model]
Llama 2 [paper] [code] [model]
Code LLama [paper] [code] [model]
RRTF [paper]
RLAIF [paper]
WikiSQL [paper] [code] [dataset]
Spider [paper] [code] [dataset]
SParC [paper] [code] [dataset]
CSpider [paper] [code] [dataset]
CoSQL [paper] [code] [dataset]
CHASE [paper] [code] [dataset]
BIRD-SQL [paper] [code] [dataset]
Execution Accuracy (EX) [paper]
Exact Match (EM) [paper]