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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 326350 of 359 papers

TitleStatusHype
GLIMPSE: Pragmatically Informative Multi-Document Summarization for Scholarly ReviewsCode0
GlobeSumm: A Challenging Benchmark Towards Unifying Multi-lingual, Cross-lingual and Multi-document News SummarizationCode0
SupMMD: A Sentence Importance Model for Extractive Summarization using Maximum Mean DiscrepancyCode0
PDSum: Prototype-driven Continuous Summarization of Evolving Multi-document Sets StreamCode0
DESCGEN: A Distantly Supervised Datasetfor Generating Entity DescriptionsCode0
Adapting the Neural Encoder-Decoder Framework from Single to Multi-Document SummarizationCode0
Hierarchical Transformers for Multi-Document SummarizationCode0
Automated Metrics for Medical Multi-Document Summarization Disagree with Human EvaluationsCode0
How "Multi" is Multi-Document Summarization?Code0
CQASUMM: Building References for Community Question Answering Summarization CorporaCode0
PELMS: Pre-training for Effective Low-Shot Multi-Document SummarizationCode0
Improving Fairness of Large Language Models in Multi-document SummarizationCode0
Which Information Matters? Dissecting Human-written Multi-document Summaries with Partial Information DecompositionCode0
Coverage-based Fairness in Multi-document SummarizationCode0
SgSum:Transforming Multi-document Summarization into Sub-graph SelectionCode0
Shaping Political Discourse using multi-source News SummarizationCode0
Pre-training Meets Clustering: A Hybrid Extractive Multi-document Summarization ModelCode0
Auto-hMDS: Automatic Construction of a Large Heterogeneous Multilingual Multi-Document Summarization CorpusCode0
Multi-Document Summarization with Centroid-Based PretrainingCode0
Centroid-based Text Summarization through Compositionality of Word EmbeddingsCode0
Abstractive Multi-Document Summarization via Joint Learning with Single-Document SummarizationCode0
Global-aware Beam Search for Neural Abstractive SummarizationCode0
Bringing Structure into Summaries: Crowdsourcing a Benchmark Corpus of Concept MapsCode0
A Temporally Sensitive Submodularity Framework for Timeline SummarizationCode0
Text Generation: A Systematic Literature Review of Tasks, Evaluation, and ChallengesCode0
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