PET-SQL

Reported on 4 benchmarks across 2 tasks · 1 paper · 2 SOTA

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)· 2024-03-13
87.6
best: 89.65 (XiYan-SQL)
SOTA
PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency arXiv:2403.09732
Text-To-SQLonspider
Execution Accuracy (Test)· 2024-03-13
87.6
best: 89.65 (XiYan-SQL)
SOTA
PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency arXiv:2403.09732
Semantic Parsingonspider
Exact Match Accuracy (Test)· 2024-03-13
66.6
best: 72.4 (T5-SR)
PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency arXiv:2403.09732
Text-To-SQLonspider
Exact Match Accuracy (Test)· 2024-03-13
66.6
best: 72.4 (T5-SR)
PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency arXiv:2403.09732