Implementation of the paper Learning to Encode Text as Human-Readable Summaries using Generative Adversarial Networks.

Sources

1. Code to obtain the CNN / Daily Mail dataset (non-anonymized) for summarization. Accessed: November 20, 2019
2. Code for the ACL 2017 paper "Get To The Point: Summarization with Pointer-Generator Networks". Accessed: November 28, 2019
3. Abigail See, Peter J. Liu, Christopher D. Manning. Get To The Point: Summarization with Pointer-Generator Networks, 2017
4. Attention RNNs in Keras. Accessed: December 2, 2019
5. Jason Brownlee. Blog post: "How to Develop a Wasserstein Generative Adversarial Network (WGAN) From Scratch". Accessed: December 21, 2019