Code for the ACL 2017 paper "Get To The Point: Summarization with Pointer-Generator Networks"

pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"

Pytorch implementation of "A Deep Reinforced Model for Abstractive Summarization" paper and pointer generator network

基于transformer的指针生成网络

implementation pointer-generator-network by pytorch and python3

Pytorch implementation of "Get to the point: Get To The Point: Summarization with Pointer-Generator Networks"

The pytorch implementation of Get To The Point: Summarization with Pointer-Generator Networks.

Pytorch implementation of the ACL paper 'Get To The Point: Summarization with Pointer-Generator Networks (See et al., 2017)', adapted to a Korean dataset

Pointer Generator Network: Seq2Seq with attention, pointing and coverage mechanism for abstractive summarization.

指针生成网络的文本摘要

基于中文的营销文本生成，基于Pointer Generator Network和Converage的实现，此外还尝试各种文本数据增广和优化技巧

An implementation of pointer generator network by using bert as encoder and transformer decoder.

Pytorch implementation of Get To The Point: Summarization with Pointer-Generator Networks (2017) by Abigail See et al.

Summarization with Pointer-Generator Networks

Long text summarization using pointer generator networks

Summarizes documents using RNN,Transformer(based on pointer generator network)

Pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"

Tensorflow 2.0 tutorials for RNN based architectures for textual problems

This is the code for the paper "Enhancing a Text Summarization System with ELMo" where we apply ELMo embeddings to pointer-generator networks for text summarization.

Chainer implementation of pointer generator networks

Code for improving the CL 2017 paper "Get To The Point: Summarization with Pointer-Generator Networks." Different forms of word embeddings are integrated into the text summarization model.

A pytorch lightning version of Pointer Generator Networks

resources for the paper 'Get To The Point: Summarization with Pointer-Generator Networks' with python3.x. overview on the post http://www.abigailsee.com/2017/04/16/taming-rnns-for-better-summarization.html or

A pipeline that summarizes text using a hybrid model of extractive and abstractive text summarization techniques.

Get to The Point: Summarization with Pointer-Generator Networks

An extension for pointer-generator network in Abstractive Text Summerization.

Reproduce and Develop the ACL 2017 paper "Get To The Point: Summarization with Pointer-Generator Networks"

A seq2seq neural network model based on multi-head self-attention mechanism at encoding stage and adopting pointer generator, coverage mechanism at decoding stage to handle out of vocabulary and repetition words.

The pointer-generator network does a better job at copying words from the source text. Additionally it also is able to copy out-of-vocabulary words allowing the algorithm to handle unseen words even if the corpus has a smaller vocabulary.

Summarization with Pointer-Generator Networks