Sentence Summarization
19 papers with code • 0 benchmarks • 0 datasets
Generating a summary of a given sentence.
Benchmarks
These leaderboards are used to track progress in Sentence Summarization
Latest papers
Positional Encoding to Control Output Sequence Length
takase/control-length
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NAACL 2019
Neural encoder-decoder models have been successful in natural language generation tasks.
Unsupervised Abstractive Sentence Summarization using Length Controlled Variational Autoencoder
In this work we present an unsupervised approach to summarize sentences in abstractive way using Variational Autoencoder (VAE).
Sequential Copying Networks
Copying mechanism shows effectiveness in sequence-to-sequence based neural network models for text generation tasks, such as abstractive sentence summarization and question generation.
Data-driven Summarization of Scientific Articles
jananiarunachalam/Research-Paper-Summarization
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Data-driven approaches to sequence-to-sequence modelling have been successfully applied to short text summarization of news articles.
A Regularized Framework for Sparse and Structured Neural Attention
vene/sparse-structured-attention
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NeurIPS 2017
Modern neural networks are often augmented with an attention mechanism, which tells the network where to focus within the input.
Selective Encoding for Abstractive Sentence Summarization
We propose a selective encoding model to extend the sequence-to-sequence framework for abstractive sentence summarization.
Online and Linear-Time Attention by Enforcing Monotonic Alignments
craffel/mad
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ICML 2017
Recurrent neural network models with an attention mechanism have proven to be extremely effective on a wide variety of sequence-to-sequence problems.
Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond
theamrzaki/text_summurization_abstractive_methods
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CONLL 2016
In this work, we model abstractive text summarization using Attentional Encoder-Decoder Recurrent Neural Networks, and show that they achieve state-of-the-art performance on two different corpora.
A Neural Attention Model for Abstractive Sentence Summarization
tensorflow/models
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EMNLP 2015
Summarization based on text extraction is inherently limited, but generation-style abstractive methods have proven challenging to build.
