Statements (25)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:convolutional_neural_network
|
| gptkbp:addressedProblem |
factual inaccuracies in abstractive summarization
out-of-vocabulary words in summarization |
| gptkbp:architecture |
hybrid model
|
| gptkbp:attentionMechanism |
yes
|
| gptkbp:citation |
https://arxiv.org/abs/1704.04368
Get To The Point: Summarization with Pointer-Generator Networks |
| gptkbp:combines |
sequence-to-sequence model
pointer network |
| gptkbp:enables |
copying words from source text
generating novel words |
| https://www.w3.org/2000/01/rdf-schema#label |
Pointer-Generator Networks
|
| gptkbp:introduced |
gptkb:Christopher_D._Manning
gptkb:Peter_J._Liu Abigail See |
| gptkbp:introducedIn |
2017
|
| gptkbp:output |
abstractive summary
extractive summary |
| gptkbp:platform |
encoder-decoder
|
| gptkbp:publishedIn |
gptkb:ACL_2017
|
| gptkbp:trainer |
gptkb:CNN/Daily_Mail
|
| gptkbp:usedFor |
text summarization
sequence-to-sequence learning |
| gptkbp:bfsParent |
gptkb:CNN/Daily_Mail
|
| gptkbp:bfsLayer |
7
|