Papers with Transformer-based data-to-text generation model

1 papers
Enhanced Transformer Model for Data-to-Text Generation (D19-56)

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Challenge: Neural models have shown significant progress on data-to-text generation tasks . data- to-text models generate descriptive texts from non-linguistic structured data .
Approach: They propose a new data-to-text generation model which learns content selection and summary generation in an end-to end fashion.
Outcome: The proposed model outperforms current state-of-the-art models on content selection precision and content ordering metrics.

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