Text Classification On R52
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy | Paper Title | Repository |
|---|---|---|---|
| Our Model* | 94.6 | Text Level Graph Neural Network for Text Classification | - |
| SGCN | 94.0 | Simplifying Graph Convolutional Networks | - |
| GraphStar | 95.00 | Graph Star Net for Generalized Multi-Task Learning | - |
| TM-Glove | 89.14 | Enhancing Interpretable Clauses Semantically using Pretrained Word Representation | - |
| 1-6 BertGCN | 96.6 | BertGCN: Transductive Text Classification by Combining GCN and BERT | - |
| SSGC | 94.5 | Simple Spectral Graph Convolution | |
| Text GCN | 93.56 | Graph Convolutional Networks for Text Classification | - |
| SGC | 94.0 | Simplifying Graph Convolutional Networks | - |
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