Extreme Summarization
11 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
Latest papers
WikiDes: A Wikipedia-Based Dataset for Generating Short Descriptions from Paragraphs
In this paper, we introduce WikiDes, a novel dataset to generate short descriptions of Wikipedia articles for the problem of text summarization.
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.
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.
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.
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.
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.
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.
TLDR: Extreme Summarization of Scientific Documents
We introduce TLDR generation, a new form of extreme summarization, for scientific papers.
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?''.
Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization
EdinburghNLP/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.
