Data To Text Generation On Rotowire Content
Metrics
DLD
Results
Performance results of various models on this benchmark
| Paper Title | ||
|---|---|---|
| Hierarchical Transformer Encoder + conditional copy | 18.90% | A Hierarchical Model for Data-to-Text Generation |
| Neural Content Planning + conditional copy | 18.58% | Data-to-Text Generation with Content Selection and Planning |
| Macro | 17.7% | Data-to-text Generation with Macro Planning |
| Force-Copy | 17.26% | May the Force Be with Your Copy Mechanism: Enhanced Supervised-Copy Method for Natural Language Generation |
| Encoder-decoder + conditional copy | 8.68% | Challenges in Data-to-Document Generation |
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