Papers with template-based input representation
Improving Compositional Generalization with Self-Training for Data-to-Text Generation (2022.acl-long)
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| Challenge: | Data-to-text generation focuses on generating fluent natural language responses from structured meaning representations (MRs). |
| Approach: | They propose a template-based input representation that greatly improves the model’s generalization capability. |
| Outcome: | The proposed model improves tree accuracy by 46%+ and reduces slot error rates by 73%+ over the strong baselines on SGD and Weather benchmarks. |