Math Word Problem Solving On Math23K
Métriques
Accuracy (training-test)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy (training-test) |
|---|---|
| athena-mathematical-reasoning-with-thought | 84.4 |
| Modèle 2 | - |
| generate-rank-a-multi-task-framework-for-math | 85.4 |
| an-expression-tree-decoding-strategy-for | 86.2 |
| Modèle 5 | 85.2 |
| graph-to-tree-learning-for-solving-math-word | 77.4 |
| multi-view-reasoning-consistent-contrastive | 87.1 |
| semantically-aligned-universal-tree | - |
| learning-by-fixing-solving-math-word-problems | - |
| athena-mathematical-reasoning-with-thought | 86.5 |
| recall-and-learn-a-memory-augmented-solver | 82.3 |
| learning-to-reason-deductively-math-word | - |
| modeling-intra-relation-in-math-word-problems | 69.5 |
| mwp-bert-a-strong-baseline-for-math-word | 84.7 |
| mwptoolkit-an-open-source-framework-for-deep | - |
| teaching-inspired-integrated-prompting | - |
| Modèle 17 | 66.9 |
| a-goal-driven-tree-structured-neural-model | - |
| deep-neural-solver-for-math-word-problems | - |