SOTAVerified

Extractive Text Summarization

Given a document, selecting a subset of the words or sentences which best represents a summary of the document.

Papers

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Showing 51–95 of 95 papers

TitleStatusHype
Scaling Up Summarization: Leveraging Large Language Models for Long Text Extractive Summarization—0
Summary Level Training of Sentence Rewriting for Abstractive Summarization—0
Topic Modeling Based Extractive Text Summarization—0
Towards a Reliable and Robust Methodology for Crowd-Based Subjective Quality Assessment of Query-Based Extractive Text Summarization—0
Towards automatic extractive text summarization of A-133 Single Audit reports with machine learning—0
Towards Supervised Extractive Text Summarization via RNN-based Sequence Classification—0
Twitter Topic Summarization by Ranking Tweets using Social Influence and Content Quality—0
Unity in Diversity: Learning Distributed Heterogeneous Sentence Representation for Extractive Summarization—0
Using Document Summarization Techniques for Speech Data Subset Selection—0
Using Statistical and Semantic Models for Multi-Document Summarization—0
Using Supervised Bigram-based ILP for Extractive Summarization—0
HiStruct+: Improving Extractive Text Summarization with Hierarchical Structure Information—0
Abstractive Text-Image Summarization Using Multi-Modal Attentional Hierarchical RNN—0
Abstractive Text Summarization for Sanskrit Prose: A Study of Methods and Approaches—0
A Dynamic Programming Algorithm for Tree Trimming-based Text Summarization—0
A Hierarchical Structured Self-Attentive Model for Extractive Document Summarization (HSSAS)—0
A Hybrid PSO-GA for Extractive Text Summarization—0
A New Persian Text Summarization Approach Based on Natural Language Processing and Graph Similarity—0
A Novel System for Extractive Clinical Note Summarization using EHR Data—0
A New Sentence Extraction Strategy for Unsupervised Extractive Summarization Methods—0
A study of semantic augmentation of word embeddings for extractive summarization—0
A topic-based sentence representation for extractive text summarization—0
At Which Level Should We Extract? An Empirical Analysis on Extractive Document Summarization—0
BoWLer: A neural approach to extractive text summarization—0
Classify or Select: Neural Architectures for Extractive Document Summarization—0
Combining Word Embeddings and N-grams for Unsupervised Document Summarization—0
Considering Nested Tree Structure in Sentence Extractive Summarization with Pre-trained Transformer—0
CovSumm: an unsupervised transformer-cum-graph-based hybrid document summarization model for CORD-19—0
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation—0
Prompt-based Pseudo-labeling Strategy for Sample-Efficient Semi-Supervised Extractive Summarization—0
Enhancing Extractive Text Summarization with Topic-Aware Graph Neural Networks—0
Exploring Domain Shift in Extractive Text Summarization—0
Extractive Multi Document Summarization using Dynamical Measurements of Complex Networks—0
Extractive Text Summarization Using Generalized Additive Models with Interactions for Sentence Selection—0
Extractive Text Summarization using Neural Networks—0
Extractive Text Summarization with Latent Topics using Heterogeneous Graph Neural Network—0
Frame Semantic-Enhanced Sentence Modeling for Sentence-level Extractive Text Summarization—0
GUSUM: Graph-Based Unsupervised Summarization using Sentence-BERT and Sentence Features—0
HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization—0
Abstractive and Extractive Text Summarization using Document Context Vector and Recurrent Neural Networks—0
HiStruct+: Improving Extractive Text Summarization with Hierarchical Structure Information—0
Hybrid MemNet for Extractive Summarization—0
Improving Neural Text Summarization using Knowledge Graphs—0
Jointly Learning Salience and Redundancy by Adaptive Sentence Reranking for Extractive Summarization—0
Knowledge Graph and Deep Neural Network for Extractive Text Summarization by Utilizing Triples—0
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All datasetsCNN / Daily MailDebateSumGovReportDUC 2004DUC 2004 Task 1

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HAHSumROUGE-144.68—Unverified
2Scaled-MatchSumROUGE-144.51—Unverified
3MatchSumROUGE-144.41—Unverified
4A2SummROUGE-144.11—Unverified
5NeRoBERTaROUGE-143.86—Unverified
6BERT-ext + RLROUGE-142.76—Unverified
7PNBERTROUGE-142.69—Unverified
8HIBERTROUGE-142.37—Unverified
9HERROUGE-142.3—Unverified
10NeuSUMROUGE-141.59—Unverified
#ModelMetricClaimedVerifiedStatus
1Longformer-BaseROUGE-L57.21—Unverified
2GPT2-MediumROUGE-L53.23—Unverified
3BERT-LargeROUGE-L49.98—Unverified
#ModelMetricClaimedVerifiedStatus
1MemSum (extractive)Avg. Test Rouge159.43—Unverified
2HEPOSAvg. Test Rouge156.86—Unverified
#ModelMetricClaimedVerifiedStatus
1Pre-training-meets-Clustering-A-Hybrid-Extractive-Multi-Document-Summarization-ModelTest ROGUE-134.01—Unverified
#ModelMetricClaimedVerifiedStatus
1AbsROUGE-126.55—Unverified