Ccg Supertagging On Ccgbank
평가 지표
Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | Accuracy | Paper Title | Repository |
---|---|---|---|
Xu et al. | 93.00 | - | - |
BiLSTM-LAN | 94.7 | Hierarchically-Refined Label Attention Network for Sequence Labeling | |
Lewis et al. | 94.7 | - | - |
CVT + Multi-task + Large | 96.1 | Semi-Supervised Sequence Modeling with Cross-View Training | |
Heterogeneous Dynamic Convolutions | 96.29 | Geometry-Aware Supertagging with Heterogeneous Dynamic Convolutions | |
NeST-CCG + BERT | 96.25 | Supertagging Combinatory Categorial Grammar with Attentive Graph Convolutional Networks | |
Low supervision | 93.26 | - | - |
Vaswani et al. | 94.24 | - | - |
0 of 8 row(s) selected.