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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

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Showing 101–150 of 359 papers

TitleStatusHype
HowSumm: A Multi-Document Summarization Dataset Derived from WikiHow ArticlesCode1
Unsupervised Multi-document Summarization for News Corpus with Key Synonyms and Contextual Embeddings—0
Leveraging Attribute Conditioning for Abstractive Multi Document Summarization—0
QA-Align: Representing Cross-Text Content Overlap by Aligning Question-Answer PropositionsCode0
Dependency Structure for News Document Summarization—0
MiRANews: Dataset and Benchmarks for Multi-Resource-Assisted News SummarizationCode0
Monolingual versus Multilingual BERTology for Vietnamese Extractive Multi-Document Summarization—0
SummerTime: Text Summarization Toolkit for Non-expertsCode1
Entity-Aware Abstractive Multi-Document Summarization—0
Highlight-Transformer: Leveraging Key Phrase Aware Attention to Improve Abstractive Multi-Document Summarization—0
DESCGEN: A Distantly Supervised Datasetfor Generating Entity DescriptionsCode0
Using Query Expansion in Manifold Ranking for Query-Oriented Multi-Document SummarizationCode0
Multi-Document Summarization withDeterminantal Point Process Attention—0
TWAG: A Topic-Guided Wikipedia Abstract GeneratorCode1
AgreeSum: Agreement-Oriented Multi-Document Summarization—0
UETrice at MEDIQA 2021: A Prosper-thy-neighbour Extractive Multi-document Summarization Model—0
Efficiently Summarizing Text and Graph Encodings of Multi-Document ClustersCode1
Nutri-bullets Hybrid: Consensual Multi-document Summarization—0
Extending Multi-Document Summarization Evaluation to the Interactive SettingCode0
Transfer Learning for Sequence Generation: from Single-source to Multi-sourceCode1
Neighborhood Rough Set based Multi-document Summarization—0
BASS: Boosting Abstractive Summarization with Unified Semantic Graph—0
Analysis of GraphSum's Attention Weights to Improve the Explainability of Multi-Document Summarization—0
PoBRL: Optimizing Multi-Document Summarization by Blending Reinforcement Learning Policies—0
Error Analysis of using BART for Multi-Document Summarization: A Study for English and German LanguageCode0
Identifying Helpful Sentences in Product Reviews—0
Generating Related Work—0
MS2: Multi-Document Summarization of Medical StudiesCode1
What's in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarization—0
Nutri-bullets: Summarizing Health Studies by Composing SegmentsCode0
Multi-document Summarization using Semantic Role Labeling and Semantic Graph for Indonesian News Article—0
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: MTSQIGA—0
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 Survey—0
Topic-Centric Unsupervised Multi-Document Summarization of Scientific and News Articles—0
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 Summarization—0
Coarse-to-Fine Query Focused Multi-Document Summarization—0
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 Keywords—0
Global-aware Beam Search for Neural Abstractive SummarizationCode0
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