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.
来源:CSDN
作者:DrogoZhang
链接:https://blog.csdn.net/weixin_40400177/article/details/103589081