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A Neural Attention Model for Abstractive Sentence Summarization

TLDR; The authors apply a neural seq2seq model to sentence summarization. The model uses an attention mechanism (soft alignment).

Key Points

  • Summaries generated on the sentence level, not paragraph level
  • Summaries have fixed length output
  • Beam search decoder
  • Extractive tuning for scoring function to encourage the model to take words from the input sequence
  • Training data: Headline + first sentence pair.
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