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Abstractive Text Summarization

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

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Pay Less Attention with Lightweight and Dynamic Convolutions

ICLR 2019 pytorch/fairseq

We predict separate convolution kernels based solely on the current time-step in order to determine the importance of context elements.

ABSTRACTIVE TEXT SUMMARIZATION LANGUAGE MODELLING MACHINE TRANSLATION

Classical Structured Prediction Losses for Sequence to Sequence Learning

NAACL 2018 pytorch/fairseq

There has been much recent work on training neural attention models at the sequence-level using either reinforcement learning-style methods or by optimizing the beam.

ABSTRACTIVE TEXT SUMMARIZATION MACHINE TRANSLATION STRUCTURED PREDICTION

Get To The Point: Summarization with Pointer-Generator Networks

ACL 2017 abisee/pointer-generator

Neural sequence-to-sequence models have provided a viable new approach for abstractive text summarization (meaning they are not restricted to simply selecting and rearranging passages from the original text).

ABSTRACTIVE TEXT SUMMARIZATION

Neural Abstractive Text Summarization with Sequence-to-Sequence Models: A Survey

5 Dec 2018shibing624/pycorrector

As part of this survey, we also develop an open source library, namely Neural Abstractive Text Summarizer (NATS) toolkit, for the abstractive text summarization.

ABSTRACTIVE TEXT SUMMARIZATION LANGUAGE MODELLING MACHINE TRANSLATION

Unified Language Model Pre-training for Natural Language Understanding and Generation

NeurIPS 2019 microsoft/unilm

This paper presents a new Unified pre-trained Language Model (UniLM) that can be fine-tuned for both natural language understanding and generation tasks.

ABSTRACTIVE TEXT SUMMARIZATION LANGUAGE MODELLING QUESTION ANSWERING QUESTION GENERATION TEXT GENERATION

Unified Language Model Pre-training for Natural Language Understanding and Generation

NeurIPS 2019 microsoft/unilm

This paper presents a new Unified pre-trained Language Model (UniLM) that can be fine-tuned for both natural language understanding and generation tasks.

#2 best model for Text Summarization on GigaWord (using extra training data)

ABSTRACTIVE TEXT SUMMARIZATION DOCUMENT SUMMARIZATION LANGUAGE MODELLING QUESTION ANSWERING QUESTION GENERATION TEXT GENERATION

Deep Reinforcement Learning For Sequence to Sequence Models

24 May 2018yaserkl/RLSeq2Seq

In this survey, we consider seq2seq problems from the RL point of view and provide a formulation combining the power of RL methods in decision-making with sequence-to-sequence models that enable remembering long-term memories.

ABSTRACTIVE TEXT SUMMARIZATION DECISION MAKING MACHINE TRANSLATION

Text Summarization with Pretrained Encoders

IJCNLP 2019 nlpyang/PreSumm

For abstractive summarization, we propose a new fine-tuning schedule which adopts different optimizers for the encoder and the decoder as a means of alleviating the mismatch between the two (the former is pretrained while the latter is not).

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

ABSTRACTIVE TEXT SUMMARIZATION DOCUMENT SUMMARIZATION EXTRACTIVE DOCUMENT SUMMARIZATION

Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting

ACL 2018 ChenRocks/fast_abs_rl

Inspired by how humans summarize long documents, we propose an accurate and fast summarization model that first selects salient sentences and then rewrites them abstractively (i. e., compresses and paraphrases) to generate a concise overall summary.

ABSTRACTIVE TEXT SUMMARIZATION

Encode, Tag, Realize: High-Precision Text Editing

IJCNLP 2019 google-research/lasertagger

We propose LaserTagger - a sequence tagging approach that casts text generation as a text editing task.

ABSTRACTIVE TEXT SUMMARIZATION TEXT GENERATION