Command Palette
Search for a command to run...
Grammatical Error Correction On Jfleg
Metrics
GLEU
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| VERNet | 62.1 | Neural Quality Estimation with Multiple Hypotheses for Grammatical Error Correction | |
| Transformer + Pre-train with Pseudo Data + BERT | 62.0 | Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction | |
| SMT + BiGRU | 61.5 | Near Human-Level Performance in Grammatical Error Correction with Hybrid Machine Translation | - |
| Copy-augmented Model (4 Ensemble +Denoising Autoencoder) | 61.0 | Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data | |
| Transformer | 59.9 | Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task | |
| CNN Seq2Seq | 57.47 | A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction |
0 of 6 row(s) selected.