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Multi-Document Summarization

Multi-Document Summarization is a process of representing a set of documents with a short piece of text by capturing the relevant information and filtering out the redundant information. Two prominent approaches to Multi-Document Summarization are extractive and abstractive summarization. Extractive summarization systems aim to extract salient snippets, sentences or passages from documents, while abstractive summarization systems aim to concisely paraphrase the content of the documents.

Source: Multi-Document Summarization using Distributed Bag-of-Words Model

Papers

Showing 126150 of 359 papers

TitleStatusHype
Identifying Helpful Sentences in Product Reviews0
Generating Related Work0
MS2: Multi-Document Summarization of Medical StudiesCode1
What's in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarization0
Nutri-bullets: Summarizing Health Studies by Composing SegmentsCode0
Multi-document Summarization using Semantic Role Labeling and Semantic Graph for Indonesian News Article0
Data Augmentation for Abstractive Query-Focused Multi-Document SummarizationCode1
ELSKE: Efficient Large-Scale Keyphrase ExtractionCode0
A novel extractive multi-document text summarization system using quantum-inspired genetic algorithm: MTSQIGA0
Neural Abstractive Multi-Document Summarization: Hierarchical or Flat Structure?0
Flight of the PEGASUS? Comparing Transformers on Few-shot and Zero-shot Multi-document Abstractive SummarizationCode0
Multi-document Summarization via Deep Learning Techniques: A Survey0
Topic-Centric Unsupervised Multi-Document Summarization of Scientific and News Articles0
WSL-DS: Weakly Supervised Learning with Distant Supervision for Query Focused Multi-Document Abstractive SummarizationCode0
Abstractive Multi-Document Summarization via Joint Learning with Single-Document SummarizationCode0
A Spectral Method for Unsupervised Multi-Document Summarization0
Coarse-to-Fine Query Focused Multi-Document Summarization0
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific ArticlesCode1
AQuaMuSe: Automatically Generating Datasets for Query-Based Multi-Document SummarizationCode1
Quantitative Argument Summarization and Beyond: Cross-Domain Key Point AnalysisCode1
SupMMD: A Sentence Importance Model for Extractive Summarization using Maximum Mean DiscrepancyCode0
Corpora Evaluation and System Bias Detection in Multi-document SummarizationCode0
Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement LearningCode1
Unsupervised Summarization by Jointly Extracting Sentences and Keywords0
Global-aware Beam Search for Neural Abstractive SummarizationCode0
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