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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
Automated Metrics for Medical Multi-Document Summarization Disagree with Human EvaluationsCode0
BERT-VBD: Vietnamese Multi-Document Summarization Framework0
Benchmarking LLMs on the Semantic Overlap Summarization Task0
An Entity-Focused Approach to Generating Company Descriptions0
BASS: Boosting Abstractive Summarization with Unified Semantic Graph0
Extending a Single-Document Summarizer to Multi-Document: a Hierarchical Approach0
Automatic Related Work Generation: A Meta Study0
An Assessment of the Accuracy of Automatic Evaluation in Summarization0
Exploring the limits of a base BART for multi-document summarization in the medical domain0
Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval0
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