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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 111120 of 359 papers

TitleStatusHype
A Multi-Document Coverage Reward for RELAXed Multi-Document SummarizationCode0
Automatic Related Work Generation: A Meta Study0
PeerSum: A Peer Review Dataset for Abstractive Multi-document Summarization0
A Multi-Document Coverage Reward for RELAXed Multi-Document Summarization0
Monolingual vs multilingual BERTology for Vietnamese extractive multi-document summarization0
SgSum:Transforming Multi-document Summarization into Sub-graph SelectionCode0
SgSum: Transforming Multi-document Summarization into Sub-graph Selection0
Topic-Guided Abstractive Multi-Document Summarization0
3M:Multi-document Summarization Considering Main and Minor Relationship0
Modeling Endorsement for Multi-Document Abstractive SummarizationCode0
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