Data To Text Generation On Mlb Dataset
평가 지표
Precision
count
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | Precision | count | Paper Title | Repository |
---|---|---|---|---|
ENT | 81.1 | 23.8 | Data-to-text Generation with Macro Planning | |
Macro | 94.4 | 30.8 | Data-to-text Generation with Macro Planning | |
Force-Copy | 84.50 | 21.05 | May the Force Be with Your Copy Mechanism: Enhanced Supervised-Copy Method for Natural Language Generation | - |
SeqPlan | 95.9 | 28.9 | Data-to-text Generation with Variational Sequential Planning |
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