Papers with macro planning stage

1 papers
Data-to-text Generation with Macro Planning (2021.tacl-1)

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Challenge: Recent approaches to data-to-text generation adopt the encoder-decoder architecture . however, these models perform poorly at selecting appropriate content and ordering it coherently .
Approach: They propose a neural model with a macro planning stage followed by a generation stage . they use data from databases of records, simulations of physical systems, accounting spreadsheets .
Outcome: The proposed model outperforms baselines on two data-to-text benchmarks . it uses the encoderdecoder architecture and is compared with existing models .

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