Command Palette
Search for a command to run...
Data To Text Generation On Rotowire Relation
Metrics
Precision
count
Results
Performance results of various models on this benchmark
| Paper Title | Repository | |||
|---|---|---|---|---|
| SeqPlan | 97.6 | 46.7 | Data-to-text Generation with Variational Sequential Planning | |
| Macro | 97.6 | 42.1 | Data-to-text Generation with Macro Planning | |
| Force-Copy | 95.40% | 27.37 | May the Force Be with Your Copy Mechanism: Enhanced Supervised-Copy Method for Natural Language Generation | - |
| Hierarchical Transformer Encoder + conditional copy | 89.46% | 21.17 | A Hierarchical Model for Data-to-Text Generation | |
| Neural Content Planning + conditional copy | 87.47% | 34.28 | Data-to-Text Generation with Content Selection and Planning | |
| Encoder-decoder + conditional copy | 74.80% | 23.72 | Challenges in Data-to-Document Generation |
0 of 6 row(s) selected.