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
Jointly Learning Salience and Redundancy by Adaptive Sentence Reranking for Extractive Summarization0
MemSum: Extractive Summarization of Long Documents Using Multi-Step Episodic Markov Decision ProcessesCode1
Topic Modeling Based Extractive Text Summarization0
CX DB8: A queryable extractive summarizer and semantic search engineCode1
Knowledge Graph and Deep Neural Network for Extractive Text Summarization by Utilizing Triples0
DebateSum: A large-scale argument mining and summarization datasetCode1
Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network0
Improving Neural Text Summarization using Knowledge Graphs0
Unsupervised Extractive Summarization by Pre-training Hierarchical TransformersCode1
Enhancing Extractive Text Summarization with Topic-Aware Graph Neural Networks0
MultiGBS: A multi-layer graph approach to biomedical summarization0
Towards a Reliable and Robust Methodology for Crowd-Based Subjective Quality Assessment of Query-Based Extractive Text Summarization0
Abstractive Text Summarization for Sanskrit Prose: A Study of Methods and Approaches0
Screenplay Summarization Using Latent Narrative StructureCode1
Heterogeneous Graph Neural Networks for Extractive Document SummarizationCode1
Combining Word Embeddings and N-grams for Unsupervised Document Summarization0
Extractive Summarization as Text MatchingCode1
Probabilistic Model of Narratives Over Topical Trends in Social Media: A Discrete Time Model0
AREDSUM: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document SummarizationCode1
At Which Level Should We Extract? An Empirical Analysis on Extractive Document Summarization0
Hybrid MemNet for Extractive Summarization0
Unity in Diversity: Learning Distributed Heterogeneous Sentence Representation for Extractive Summarization0
Extractive Multi-document Summarization using K-means, Centroid-based Method, MMR, and Sentence PositionCode0
Towards Supervised Extractive Text Summarization via RNN-based Sequence Classification0
Towards automatic extractive text summarization of A-133 Single Audit reports with machine learning0
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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