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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 76–100 of 359 papers

TitleStatusHype
Abstractive Unsupervised Multi-Document Summarization using Paraphrastic Sentence Fusion—0
Content based Weighted Consensus Summarization—0
Concept-Map-Based Multi-Document Summarization using Concept Coreference Resolution and Global Importance Optimization—0
Abstractive Multi-document Summarization by Partial Tree Extraction, Recombination and Linearization—0
Exploiting Category-Specific Information for Multi-Document Summarization—0
Exploring the limits of a base BART for multi-document summarization in the medical domain—0
Controllable Multi-document Summarization: Coverage & Coherence Intuitive Policy with Large Language Model Based Rewards—0
A Redundancy-Aware Sentence Regression Framework for Extractive Summarization—0
A Hybrid Approach to Multi-document Summarization of Opinions in Reviews—0
Creation and use of Language Resources in a Question-Answering eHealth System—0
A Preliminary Study of Tweet Summarization using Information Extraction—0
Complex Question Answering: Unsupervised Learning Approaches and Experiments—0
Deconstructing Human Literature Reviews -- A Framework for Multi-Document Summarization—0
Deep Attentive Sentence Ordering Network—0
A Sentence Compression Based Framework to Query-Focused Multi-Document Summarization—0
Detection of Topic and its Extrinsic Evaluation Through Multi-Document Summarization—0
Discriminative Marginalized Probabilistic Neural Method for Multi-Document Summarization of Medical Literature—0
A Spectral Method for Unsupervised Multi-Document Summarization—0
Document-aware Positional Encoding and Linguistic-guided Encoding for Abstractive Multi-document Summarization—0
Do Multi-Document Summarization Models Synthesize?—0
Drug Extraction from the Web: Summarizing Drug Experiences with Multi-Dimensional Topic Models—0
DualSum: a Topic-Model based approach for update summarization—0
AgreeSum: Agreement-Oriented Multi-Document Summarization—0
Combining State-of-the-Art Models with Maximal Marginal Relevance for Few-Shot and Zero-Shot Multi-Document Summarization—0
Coarse-to-Fine Query Focused Multi-Document Summarization—0
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