Table Based Fact Verification On Tabfact
Métriques
Test
Val
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Test | Val |
|---|---|---|
| understanding-tables-with-intermediate-pre | 81.0 | 81.0 |
| pasta-table-operations-aware-fact | 89.3 | 89.2 |
| unifiedskg-unifying-and-multi-tasking | 83.68 | 83.97 |
| tabfact-a-large-scale-dataset-for-table-based | 65.12 | 66.1 |
| advanced-reasoning-and-transformation-engine | 93.1 | - |
| binding-language-models-in-symbolic-languages | 86.0 | - |
| tabsqlify-enhancing-reasoning-capabilities-of | 79.5 | - |
| reastap-injecting-table-reasoning-skills | 84.9 | 84.6 |
| chain-of-table-evolving-tables-in-the | 86.61 | - |
| efficient-prompting-for-llm-based-generative | 85.77 | - |
| tapex-table-pre-training-via-learning-a | 84.2 | 84.6 |
| normtab-improving-symbolic-reasoning-in-llms | 68.90 | - |
| tabfact-a-large-scale-dataset-for-table-based | 50.5 | 50.9 |
| large-language-models-are-versatile | 93.0 | - |
| table-based-fact-verification-with-salience | 82.1 | 82.7 |