Keeping Notes: Conditional Natural Language Generation with a Scratchpad Encoder (P19-1)
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| Challenge: | Qualitative assessments in the form of human judgements (question generation), attention visualization (MT), and sample output (summarization) provide further evidence of the ability of Scratchpad to generate fluent and expressive output. |
| Approach: | They propose to use the encoder as a "scratchpad" memory to keep track of what has been generated and guide future generation. |
| Outcome: | The proposed mechanism improves the fluency of seq2seq models on three well-studied natural language generation tasks. |
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| Challenge: | Recent work on abstractive summarization has made progress with neural encoder-decoder architectures, but these models lack explicit semantic modeling of the source document and its summary. |
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| Challenge: | Pre-trained language model representations have been successful in a wide range of language understanding tasks. |
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Pre-training for Abstractive Document Summarization by Reinstating Source Text (2020.emnlp-main)
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