SOTAVerified

Extractive Text Summarization

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

Papers

Showing 2650 of 95 papers

TitleStatusHype
GUSUM: Graph-based Unsupervised Summarization Using Sentence Features Scoring and Sentence-BERTCode0
Pre-training Meets Clustering: A Hybrid Extractive Multi-document Summarization ModelCode0
Ranking Sentences for Extractive Summarization with Reinforcement LearningCode0
Discourse-Aware Neural Extractive Text SummarizationCode0
Reading Like HER: Human Reading Inspired Extractive SummarizationCode0
Document Modeling with External Attention for Sentence ExtractionCode0
Centroid-based Text Summarization through Compositionality of Word EmbeddingsCode0
IDN-Sum: A New Dataset for Interactive Digital Narrative Extractive Text SummarisationCode0
Searching for Effective Neural Extractive Summarization: What Works and What's NextCode0
Language Model Pre-training for Hierarchical Document Representations0
Learning with fuzzy hypergraphs: a topical approach to query-oriented text summarization0
A Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches0
Monolingual versus Multilingual BERTology for Vietnamese Extractive Multi-Document Summarization0
MultiGBS: A multi-layer graph approach to biomedical summarization0
Multi-layered graph-based multi-document summarization model0
Multi Perspective Scientific Document Summarization With Graph Attention Networks (GATS)0
Multiplex Graph Neural Network for Extractive Text Summarization0
Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network0
Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization0
Neural Latent Extractive Document Summarization0
Probabilistic Model of Narratives Over Topical Trends in Social Media: A Discrete Time Model0
RankSum An unsupervised extractive text summarization based on rank fusion0
Revisiting the Centroid-based Method: A Strong Baseline for Multi-Document Summarization0
Revisiting the Centroid-based Method: A Strong Baseline for Multi-Document Summarization0
San-BERT: Extractive Summarization for Sanskrit Documents using BERT and it's variants0
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Benchmark Results

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