MAPO + TABERTLarge (K = 3)

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 ParsingonWikiTableQuestions
Accuracy (Dev)· 2020-05-17
52.2
best: 65 (Binder)
SOTA
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data arXiv:2005.08314
Semantic ParsingonWikiTableQuestions
Accuracy (Test)· 2020-05-17
51.8
best: 80.8 (ARTEMIS-DA)
SOTA
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data arXiv:2005.08314
Semantic Parsingonspider
Exact Match Accuracy (Dev)· 2020-05-17
64.5
best: 81.6 (datagpt-sql-7B + InvalidSQL-Feedback)
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data arXiv:2005.08314
Text-To-SQLonspider
Exact Match Accuracy (Dev)· 2020-05-17
64.5
best: 81.6 (datagpt-sql-7B + InvalidSQL-Feedback)
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data arXiv:2005.08314