Unsupervised Extractive Summarization
16 papers with code • 3 benchmarks • 4 datasets
Pubmed
FacetSum
XWikiRef
Most implemented papers
A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents
acohan/long-summarization
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NAACL 2018
Neural abstractive summarization models have led to promising results in summarizing relatively short documents.
Combining Graph Degeneracy and Submodularity for Unsupervised Extractive Summarization
We present a fully unsupervised, extractive text summarization system that leverages a submodularity framework introduced by past research.
Plain English Summarization of Contracts
We propose the task of summarizing such legal documents in plain English, which would enable users to have a better understanding of the terms they are accepting.
Sentence Centrality Revisited for Unsupervised Summarization
Single document summarization has enjoyed renewed interests in recent years thanks to the popularity of neural network models and the availability of large-scale datasets.
Discourse-Aware Unsupervised Summarization of Long Scientific Documents
We propose an unsupervised graph-based ranking model for extractive summarization of long scientific documents.
Unsupervised Extractive Summarization by Pre-training Hierarchical Transformers
xssstory/STAS
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Findings of the Association for Computational Linguistics 2020
We also find in experiments that our model is less dependent on sentence positions.
Unsupervised Abstractive Summarization of Bengali Text Documents
tafseer-nayeem/BengaliSummarization
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EACL 2021
We also provide a human-annotated dataset with document-summary pairs to evaluate our abstractive model and to support the comparison of future abstractive summarization systems of the Bengali Language.
Unsupervised Extractive Summarization using Pointwise Mutual Information
vishakhpk/mi-unsup-summ
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EACL 2021
Unsupervised approaches to extractive summarization usually rely on a notion of sentence importance defined by the semantic similarity between a sentence and the document.
Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
Faceted summarization provides briefings of a document from different perspectives.
Unsupervised Extractive Summarization-Based Representations for Accurate and Explainable Collaborative Filtering
reinaldncku/escofilt
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ACL 2021
Our explainability study demonstrates the superiority of and preference for summary-level explanations over other explanation types.
