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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 8190 of 359 papers

TitleStatusHype
Fair Summarization: Bridging Quality and Diversity in Extractive SummariesCode0
Corpora Evaluation and System Bias Detection in Multi-document SummarizationCode0
Generating Wikipedia by Summarizing Long SequencesCode0
ELSKE: Efficient Large-Scale Keyphrase ExtractionCode0
Hierarchical Transformers for Multi-Document SummarizationCode0
Bringing Structure into Summaries: Crowdsourcing a Benchmark Corpus of Concept MapsCode0
Error Analysis of using BART for Multi-Document Summarization: A Study for English and German LanguageCode0
Bridging the gap between extractive and abstractive summaries: Creation and evaluation of coherent extracts from heterogeneous sourcesCode0
Scoring Sentence Singletons and Pairs for Abstractive SummarizationCode0
Beyond Generic Summarization: A Multi-faceted Hierarchical Summarization Corpus of Large Heterogeneous DataCode0
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