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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 301–325 of 359 papers

TitleStatusHype
Combining State-of-the-Art Models with Maximal Marginal Relevance for Few-Shot and Zero-Shot Multi-Document Summarization—0
Complex Question Answering: Unsupervised Learning Approaches and Experiments—0
Concept-Map-Based Multi-Document Summarization using Concept Coreference Resolution and Global Importance Optimization—0
Content based Weighted Consensus Summarization—0
Controllable Multi-document Summarization: Coverage & Coherence Intuitive Policy with Large Language Model Based Rewards—0
Creation and use of Language Resources in a Question-Answering eHealth System—0
Data-driven Paraphrasing and Stylistic Harmonization—0
Deconstructing Human Literature Reviews -- A Framework for Multi-Document Summarization—0
Deep Attentive Sentence Ordering Network—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
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
Efficient Online Summarization of Microblogging Streams—0
Empirical analysis of exploiting review helpfulness for extractive summarization of online reviews—0
End-to-end Argument Generation System in Debating—0
Entity-Aware Abstractive Multi-Document Summarization—0
Entity-Supported Summarization of Biomedical Abstracts—0
Evaluating Pre-Trained Language Models on Multi-Document Summarization for Literature Reviews—0
EventSum: A Large-Scale Event-Centric Summarization Dataset for Chinese Multi-News Documents—0
Evolutionary Hierarchical Dirichlet Process for Timeline Summarization—0
ExB Text Summarizer—0
Exploiting Category-Specific Information for Multi-Document Summarization—0
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