Papers with realization
Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation (N19-1)
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| Challenge: | Modern neural generation systems conflate these two steps into a single end-to-end differentiable system. |
| Approach: | They propose to split the generation process into a symbolic text-planning stage that is faithful to the input, followed by a neural generation stage that focuses only on realization. |
| Outcome: | The proposed method improves reliability and adequacy while maintaining fluent output. |
Nutri-bullets Hybrid: Consensual Multi-document Summarization (2021.naacl-main)
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| Challenge: | Existing methods for generating comparative summaries that highlight similarities and contradictions in input documents are lacking large parallel training data for their training. |
| Approach: | They propose a method for generating comparative summaries that highlight similarities and contradictions in input documents by using a neural interpretation of traditional concept-to-text generation systems. |
| Outcome: | The proposed model is compared with conventional methods in the domain of nutrition and health, where the existing models lack large parallel training data. |