Extreme Summarization
12 papers with code • 4 benchmarks • 7 datasets
Image credit: TLDR: Extreme Summarization of Scientific Documents
Libraries
Use these libraries to find Extreme Summarization models and implementations
GEM
XSum
SciTLDR
CiteSum
TLDR9+
SummZoo
Most implemented papers
A Convolutional Attention Network for Extreme Summarization of Source Code
Attention mechanisms in neural networks have proved useful for problems in which the input and output do not have fixed dimension.
ByT5: Towards a token-free future with pre-trained byte-to-byte models
Most widely-used pre-trained language models operate on sequences of tokens corresponding to word or subword units.
TLDR: Extreme Summarization of Scientific Documents
We introduce TLDR generation, a new form of extreme summarization, for scientific papers.
Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization
shashiongithub/XSum
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EMNLP 2018
We introduce extreme summarization, a new single-document summarization task which does not favor extractive strategies and calls for an abstractive modeling approach.
IndicBART: A Pre-trained Model for Indic Natural Language Generation
We present IndicBART, a multilingual, sequence-to-sequence pre-trained model focusing on 11 Indic languages and English.
What is this Article about? Extreme Summarization with Topic-aware Convolutional Neural Networks
We introduce 'extreme summarization', a new single-document summarization task which aims at creating a short, one-sentence news summary answering the question ``What is the article about?''.
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles
Multi-document summarization is a challenging task for which there exists little large-scale datasets.
TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts
Recent models in developing summarization systems consist of millions of parameters and the model performance is highly dependent on the abundance of training data.
CiteSum: Citation Text-guided Scientific Extreme Summarization and Domain Adaptation with Limited Supervision
Scientific extreme summarization (TLDR) aims to form ultra-short summaries of scientific papers.
X-SCITLDR: Cross-Lingual Extreme Summarization of Scholarly Documents
The number of scientific publications nowadays is rapidly increasing, causing information overload for researchers and making it hard for scholars to keep up to date with current trends and lines of work.
