Papers with transformer-based pointer network

1 papers
Deep Copycat Networks for Text-to-Text Generation (D19-1)

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Challenge: Text-to-text generation tasks require copying words from the input to the output.
Approach: They propose a transformer-based pointer network for text-to-text generation which generates more abstractive summaries and a further extension of this architecture for automatic post-editing.
Outcome: The proposed model outperforms existing models in text-to-text generation tasks and improves translation accuracy.

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