Extractive Text Summarization
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Benchmarks
Most implemented
Get To The Point: Summarization with Pointer-Generator Networks
Text Summarization with Pretrained Encoders
Efficient Attention: Attention with Linear Complexities
Fine-tune BERT for Extractive Summarization
Leveraging BERT for Extractive Text Summarization on Lectures
A Neural Attention Model for Abstractive Sentence Summarization
Papers
Efficient Extractive Text Summarization for Online News Articles Using Machine Learning
In the age of information overload, content management for online news articles relies on efficient summarization to enhance accessibility and user engagement. This article addresses the challenge of extractive text summ…
Extractive Text SummarizationBinary ClassificationA Novel Word Pair-based Gaussian Sentence Similarity Algorithm For Bengali Extractive Text Summarization
Extractive Text Summarization is the process of selecting the most representative parts of a larger text without losing any key information. Recent attempts at extractive text summarization in Bengali, either relied on s…
ArticlesExtractive SummarizationExtractive Text SummarizationSentence+2Scaling Up Summarization: Leveraging Large Language Models for Long Text Extractive Summarization
In an era where digital text is proliferating at an unprecedented rate, efficient summarization tools are becoming indispensable. While Large Language Models (LLMs) have been successfully applied in various NLP tasks, th…
Extractive SummarizationExtractive Text SummarizationLanguage ModelingLanguage Modelling+3A Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches
Existing approaches for low-resource text summarization primarily employ large language models (LLMs) like GPT-3 or GPT-4 at inference time to generate summaries directly; however, such approaches often suffer from incon…
Abstractive Text SummarizationData AugmentationExtractive SummarizationExtractive Text Summarization+5RankSum An unsupervised extractive text summarization based on rank fusion
In this paper, we propose Ranksum, an approach for extractive text summarization of single documents based on the rank fusion of four multi-dimensional sentence features extracted for each sentence: topic information, se…
Extractive Text SummarizationSentenceSentence EmbeddingsText Summarization+1Prompt-based Pseudo-labeling Strategy for Sample-Efficient Semi-Supervised Extractive Summarization
Semi-supervised learning (SSL) is a widely used technique in scenarios where labeled data is scarce and unlabeled data is abundant. While SSL is popular for image and text classification, it is relatively underexplored f…
Extractive SummarizationExtractive Text Summarizationtext-classificationText Classification+1