Extractive Summarization
103 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Extractive Summarization
Libraries
Use these libraries to find Extractive Summarization models and implementations
SubSumE
Most implemented papers
Screenplay Summarization Using Latent Narrative Structure
Most general-purpose extractive summarization models are trained on news articles, which are short and present all important information upfront.
CX DB8: A queryable extractive summarizer and semantic search engine
Competitive Debate's increasingly technical nature has left competitors looking for tools to accelerate evidence production.
Contextualized Rewriting for Text Summarization
baoguangsheng/ctx-rewriter-for-summ
•
•
Extractive summarization suffers from irrelevance, redundancy and incoherence.
DisCo: Distilled Student Models Co-training for Semi-supervised Text Mining
litesslhub/disco
•
•
Many text mining models are constructed by fine-tuning a large deep pre-trained language model (PLM) in downstream tasks.
OARelatedWork: A Large-Scale Dataset of Related Work Sections with Full-texts from Open Access Sources
We show that the estimated upper bound for extractive summarization increases by 217% in the ROUGE-2 score, when using full content instead of abstracts.
Neural Summarization by Extracting Sentences and Words
adrian9631/TextSumma
•
•
ACL 2016
Traditional approaches to extractive summarization rely heavily on human-engineered features.
Analyzing Pre-processing Settings for Urdu Single-document Extractive Summarization
Preprocessing is a preliminary step in many fields including IR and NLP.
DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks
In this work, we present a compact, modular framework for constructing novel recurrent neural architectures.
Neural Extractive Summarization with Side Information
Most extractive summarization methods focus on the main body of the document from which sentences need to be extracted.
