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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 51–75 of 359 papers

TitleStatusHype
A Hierarchical Encoding-Decoding Scheme for Abstractive Multi-document SummarizationCode0
Summarizing Multiple Documents with Conversational Structure for Meta-Review GenerationCode1
LBMT team at VLSP2022-Abmusu: Hybrid method with text correlation and generative models for Vietnamese multi-document summarization—0
XWikiGen: Cross-lingual Summarization for Encyclopedic Text Generation in Low Resource LanguagesCode0
Compressed Heterogeneous Graph for Abstractive Multi-Document SummarizationCode0
Automatically Summarizing Evidence from Clinical Trials: A Prototype Highlighting Current Challenges—0
Mining both Commonality and Specificity from Multiple Documents for Multi-Document Summarization—0
PDSum: Prototype-driven Continuous Summarization of Evolving Multi-document Sets StreamCode0
Generating a Structured Summary of Numerous Academic Papers: Dataset and MethodCode0
Do Multi-Document Summarization Models Synthesize?—0
Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval—0
SumREN: Summarizing Reported Speech about Events in NewsCode0
Combining State-of-the-Art Models with Maximal Marginal Relevance for Few-Shot and Zero-Shot Multi-Document Summarization—0
Moving beyond word lists: towards abstractive topic labels for human-like topics of scientific documents—0
How "Multi" is Multi-Document Summarization?Code0
Overview of MSLR2022: A Shared Task on Multi-document Summarization for Literature ReviewsCode0
Overview of the Third Workshop on Scholarly Document Processing—0
Evaluating Pre-Trained Language Models on Multi-Document Summarization for Literature Reviews—0
Exploring the limits of a base BART for multi-document summarization in the medical domain—0
An Extractive-Abstractive Approach for Multi-document Summarization of Scientific Articles for Literature ReviewCode0
UPER: Boosting Multi-Document Summarization with an Unsupervised Prompt-based ExtractorCode0
基于实体信息增强及多粒度融合的多文档摘要(Multi-Document Summarization Based on Entity Information Enhancement and Multi-Granularity Fusion)—0
Document-aware Positional Encoding and Linguistic-guided Encoding for Abstractive Multi-document Summarization—0
Parallel Hierarchical Transformer with Attention Alignment for Abstractive Multi-Document Summarization—0
Multi-Document Summarization with Centroid-Based PretrainingCode0
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