MSc-SQL

Reported on 4 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing4 results

Semantic Parsingonspider
Execution Accuracy (Test)· 2024-10-16
84.7
best: 89.65 (XiYan-SQL)
MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation arXiv:2410.12916
Semantic ParsingonBIRD (BIg Bench for LaRge-scale Database Grounded Text-to-SQL Evaluation)
Execution Accuracy % (Dev)· 2024-10-16
65.6
best: 74.32 (DSAIR + GPT-4o)
MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation arXiv:2410.12916
Text-To-SQLonspider
Execution Accuracy (Test)· 2024-10-16
84.7
best: 89.65 (XiYan-SQL)
MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation arXiv:2410.12916
Text-To-SQLonBIRD (BIg Bench for LaRge-scale Database Grounded Text-to-SQL Evaluation)
Execution Accuracy % (Dev)· 2024-10-16
65.6
best: 74.32 (DSAIR + GPT-4o)
MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation arXiv:2410.12916