Learning to Encode Text as Human-Readable Summaries using Generative Adversarial Networks

10/05/2018
by   Yau-Shian Wang, et al.
0

Auto-encoders compress input data into a latent-space representation and reconstruct the original data from the representation. This latent representation is not easily interpreted by humans. In this paper, we propose training an auto-encoder that encodes input text into human-readable sentences, and unpaired abstractive summarization is thereby achieved. The auto-encoder is composed of a generator and a reconstructor. The generator encodes the input text into a shorter word sequence, and the reconstructor recovers the generator input from the generator output. To make the generator output human-readable, a discriminator restricts the output of the generator to resemble human-written sentences. By taking the generator output as the summary of the input text, abstractive summarization is achieved without document-summary pairs as training data. Promising results are shown on both English and Chinese corpora.

READ FULL TEXT
research
10/02/2019

SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders

We propose an end-to-end neural model for zero-shot abstractive text sum...
research
11/26/2017

Generative Adversarial Network for Abstractive Text Summarization

In this paper, we propose an adversarial process for abstractive text su...
research
09/07/2018

Unsupervised Sentence Compression using Denoising Auto-Encoders

In sentence compression, the task of shortening sentences while retainin...
research
11/10/2018

Adversarially-Trained Normalized Noisy-Feature Auto-Encoder for Text Generation

This article proposes Adversarially-Trained Normalized Noisy-Feature Aut...
research
07/02/2019

Cooperative Generator-Discriminator Networks for Abstractive Summarization with Narrative Flow

We introduce Cooperative Generator-Discriminator Networks (Co-opNet), a ...
research
07/17/2018

Query-Conditioned Three-Player Adversarial Network for Video Summarization

Video summarization plays an important role in video understanding by se...
research
06/17/2020

CoSE: Compositional Stroke Embeddings

We present a generative model for stroke-based drawing tasks which is ab...

Please sign up or login with your details

Forgot password? Click here to reset