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 1–10 of 95 papers

TitleStatusHype
A Novel Word Pair-based Gaussian Sentence Similarity Algorithm For Bengali Extractive Text SummarizationCode0
Scaling Up Summarization: Leveraging Large Language Models for Long Text Extractive Summarization—0
A Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches—0
RankSum An unsupervised extractive text summarization based on rank fusion—0
Prompt-based Pseudo-labeling Strategy for Sample-Efficient Semi-Supervised Extractive Summarization—0
Pre-training Meets Clustering: A Hybrid Extractive Multi-document Summarization ModelCode0
CovSumm: an unsupervised transformer-cum-graph-based hybrid document summarization model for CORD-19—0
San-BERT: Extractive Summarization for Sanskrit Documents using BERT and it's variants—0
Align and Attend: Multimodal Summarization with Dual Contrastive LossesCode1
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation—0
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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