Document Summarization

37 papers with code · Natural Language Processing
Subtask of Text Summarization

State-of-the-art leaderboards

Greatest papers with code

Language Models are Unsupervised Multitask Learners

Preprint 2019 huggingface/pytorch-pretrained-BERT

Natural language processing tasks, such as question answering, machine translation, reading comprehension, and summarization, are typically approached with supervised learning on taskspecific datasets.

 SOTA for Language Modelling on Text8 (using extra training data)

COMMON SENSE REASONING DOCUMENT SUMMARIZATION LANGUAGE MODELLING MACHINE TRANSLATION QUESTION ANSWERING READING COMPREHENSION

Generating Wikipedia by Summarizing Long Sequences

ICLR 2018 tensorflow/tensor2tensor

We show that generating English Wikipedia articles can be approached as a multi- document summarization of source documents.

DOCUMENT SUMMARIZATION MULTI-DOCUMENT SUMMARIZATION

Fine-tune BERT for Extractive Summarization

arXiv 2019 nlpyang/BertSum

BERT (Devlin et al., 2018), a pre-trained Transformer (Vaswani et al., 2017) model, has achieved ground-breaking performance on multiple NLP tasks.

 SOTA for Document Summarization on CNN / Daily Mail (using extra training data)

DOCUMENT SUMMARIZATION EXTRACTIVE DOCUMENT SUMMARIZATION

Ranking Sentences for Extractive Summarization with Reinforcement Learning

NAACL 2018 shashiongithub/Refresh

In this paper we conceptualize extractive summarization as a sentence ranking task and propose a novel training algorithm which globally optimizes the ROUGE evaluation metric through a reinforcement learning objective.

DOCUMENT SUMMARIZATION

Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

EMNLP 2018 shashiongithub/XSum

We introduce extreme summarization, a new single-document summarization task which does not favor extractive strategies and calls for an abstractive modeling approach.

DOCUMENT SUMMARIZATION

Neural Document Summarization by Jointly Learning to Score and Select Sentences

ACL 2018 magic282/NeuSum

In this paper, we present a novel end-to-end neural network framework for extractive document summarization by jointly learning to score and select sentences.

DOCUMENT SUMMARIZATION EXTRACTIVE DOCUMENT SUMMARIZATION

SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents

14 Nov 2016kedz/nnsum

We present SummaRuNNer, a Recurrent Neural Network (RNN) based sequence model for extractive summarization of documents and show that it achieves performance better than or comparable to state-of-the-art.

DOCUMENT SUMMARIZATION