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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 1–50 of 359 papers

TitleStatusHype
Summary-Source Proposition-level Alignment: Task, Datasets and Supervised BaselineCode1
Generating (Factual?) Narrative Summaries of RCTs: Experiments with Neural Multi-Document SummarizationCode1
MS2: Multi-Document Summarization of Medical StudiesCode1
SummPip: Unsupervised Multi-Document Summarization with Sentence Graph CompressionCode1
Pre-training via ParaphrasingCode1
HowSumm: A Multi-Document Summarization Dataset Derived from WikiHow ArticlesCode1
Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News ArticlesCode1
MSˆ2: Multi-Document Summarization of Medical StudiesCode1
PeerSum: A Peer Review Dataset for Abstractive Multi-document SummarizationCode1
SummerTime: Text Summarization Toolkit for Non-expertsCode1
Summarizing Multiple Documents with Conversational Structure for Meta-Review GenerationCode1
PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document SummarizationCode1
Multi-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple GranularitiesCode1
Improving Multi-Document Summarization through Referenced Flexible Extraction with Credit-AwarenessCode1
CAiRE-COVID: A Question Answering and Query-focused Multi-Document Summarization System for COVID-19 Scholarly Information ManagementCode1
Efficiently Summarizing Text and Graph Encodings of Multi-Document ClustersCode1
HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive SummarizationCode1
LongT5: Efficient Text-To-Text Transformer for Long SequencesCode1
Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement LearningCode1
ODSum: New Benchmarks for Open Domain Multi-Document SummarizationCode1
PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document SummarizationCode1
Quantitative Argument Summarization and Beyond: Cross-Domain Key Point AnalysisCode1
Transfer Learning for Sequence Generation: from Single-source to Multi-sourceCode1
TWAG: A Topic-Guided Wikipedia Abstract GeneratorCode1
SUPERT: Towards New Frontiers in Unsupervised Evaluation Metrics for Multi-Document SummarizationCode1
Proposition-Level Clustering for Multi-Document SummarizationCode1
A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events PortalCode1
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific ArticlesCode1
AQuaMuSe: Automatically Generating Datasets for Query-Based Multi-Document SummarizationCode1
Proposition-Level Clustering for Multi-Document SummarizationCode1
Attribute First, then Generate: Locally-attributable Grounded Text GenerationCode1
Bottom-Up Abstractive SummarizationCode1
Data Augmentation for Abstractive Query-Focused Multi-Document SummarizationCode1
DynE: Dynamic Ensemble Decoding for Multi-Document SummarizationCode1
GameWikiSum: a Novel Large Multi-Document Summarization DatasetCode1
An Entity-Focused Approach to Generating Company Descriptions—0
An Assessment of the Accuracy of Automatic Evaluation in Summarization—0
3M:Multi-document Summarization Considering Main and Minor Relationship—0
Analyzing Stemming Approaches for Turkish Multi-Document Summarization—0
Analysis of GraphSum's Attention Weights to Improve the Explainability of Multi-Document Summarization—0
Adapting Neural Single-Document Summarization Model for Abstractive Multi-Document Summarization: A Pilot Study—0
Benchmarking LLMs on the Semantic Overlap Summarization Task—0
A Multi-level Annotated Corpus of Scientific Papers for Scientific Document Summarization and Cross-document Relation Discovery—0
ACM -- Attribute Conditioning for Abstractive Multi Document Summarization—0
Abstractive Multi-Document Summarization via Phrase Selection and Merging—0
A Supervised Aggregation Framework for Multi-Document Summarization—0
A Multi-Document Coverage Reward for RELAXed Multi-Document Summarization—0
A Subjective Logic Framework for Multi-Document Summarization—0
Assessing the performance of Olelo, a real-time biomedical question answering application—0
A Method of Accounting Bigrams in Topic Models—0
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