Grammatical Error Detection On Fce
Metrics
F0.5
Results
Performance results of various models on this benchmark
Model Name | F0.5 | Paper Title | Repository |
|---|---|---|---|
| VERNet | 72.2 | Neural Quality Estimation with Multiple Hypotheses for Grammatical Error Correction | - |
| Bi-LSTM + LMcost | 48.48 | Semi-supervised Multitask Learning for Sequence Labeling | - |
| Bi-LSTM | 41.1 | Compositional Sequence Labeling Models for Error Detection in Learner Writing | - |
| Bi-LSTM+ Error- and Grammaticality-Specific Word Embeddings | 44.6 | Grammatical Error Detection Using Error- and Grammaticality-Specific Word Embeddings | |
| Bi-LSTM + err POS GR | 47.7 | Auxiliary Objectives for Neural Error Detection Models | - |
| Bi-LSTM + charattn | 41.88 | Attending to Characters in Neural Sequence Labeling Models | - |
| BiLSTM-JOINT | 52.07 | Jointly Learning to Label Sentences and Tokens | - |
| Ann+PAT+MT | 49.11 | Artificial Error Generation with Machine Translation and Syntactic Patterns | - |
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