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Text Classification On R52
Metrics
Accuracy
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| 1-6 BertGCN | 96.6 | BertGCN: Transductive Text Classification by Combining GCN and BERT | |
| GraphStar | 95.00 | Graph Star Net for Generalized Multi-Task Learning | |
| Our Model* | 94.6 | Text Level Graph Neural Network for Text Classification | |
| SSGC | 94.5 | Simple Spectral Graph Convolution | - |
| SGCN | 94.0 | Simplifying Graph Convolutional Networks | |
| SGC | 94.0 | Simplifying Graph Convolutional Networks | |
| Text GCN | 93.56 | Graph Convolutional Networks for Text Classification | |
| TM-Glove | 89.14 | Enhancing Interpretable Clauses Semantically using Pretrained Word Representation |
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