Grammatical Error Detection On Fce
Metriken
F0.5
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | ||
|---|---|---|
| VERNet | 72.2 | Neural Quality Estimation with Multiple Hypotheses for Grammatical Error Correction |
| 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 |
| Bi-LSTM + LMcost | 48.48 | Semi-supervised Multitask Learning for Sequence Labeling |
| Bi-LSTM + err POS GR | 47.7 | Auxiliary Objectives for Neural Error Detection Models |
| Bi-LSTM+ Error- and Grammaticality-Specific Word Embeddings | 44.6 | Grammatical Error Detection Using Error- and Grammaticality-Specific Word Embeddings |
| Bi-LSTM + charattn | 41.88 | Attending to Characters in Neural Sequence Labeling Models |
| Bi-LSTM | 41.1 | Compositional Sequence Labeling Models for Error Detection in Learner Writing |
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