About

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

Benchmarks

TREND DATASET BEST METHOD PAPER TITLE PAPER CODE COMPARE

Datasets

Greatest papers with code

Generating Wikipedia by Summarizing Long Sequences

ICLR 2018 tensorflow/tensor2tensor

We show that generating English Wikipedia articles can be approached as a multi- document summarization of source documents.

DOCUMENT SUMMARIZATION EXTRACTIVE SUMMARIZATION MULTI-DOCUMENT SUMMARIZATION

Leveraging Graph to Improve Abstractive Multi-Document Summarization

ACL 2020 PaddlePaddle/Research

Graphs that capture relations between textual units have great benefits for detecting salient information from multiple documents and generating overall coherent summaries.

DOCUMENT SUMMARIZATION MULTI-DOCUMENT SUMMARIZATION

Hierarchical Transformers for Multi-Document Summarization

ACL 2019 nlpyang/hiersumm

In this paper, we develop a neural summarization model which can effectively process multiple input documents and distill Transformer architecture with the ability to encode documents in a hierarchical manner.

DOCUMENT SUMMARIZATION MULTI-DOCUMENT SUMMARIZATION

Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model

ACL 2019 Alex-Fabbri/Multi-News

Automatic generation of summaries from multiple news articles is a valuable tool as the number of online publications grows rapidly.

DOCUMENT SUMMARIZATION EXTRACTIVE SUMMARIZATION MULTI-DOCUMENT SUMMARIZATION

Scoring Sentence Singletons and Pairs for Abstractive Summarization

ACL 2019 ucfnlp/summarization-sing-pair-mix

There is thus a crucial gap between sentence selection and fusion to support summarizing by both compressing single sentences and fusing pairs.

ABSTRACTIVE TEXT SUMMARIZATION DOCUMENT SUMMARIZATION MULTI-DOCUMENT SUMMARIZATION SENTENCE FUSION

Pre-training via Paraphrasing

NeurIPS 2020 lucidrains/marge-pytorch

The objective noisily captures aspects of paraphrase, translation, multi-document summarization, and information retrieval, allowing for strong zero-shot performance on several tasks.

DOCUMENT SUMMARIZATION INFORMATION RETRIEVAL LANGUAGE MODELLING MULTI-DOCUMENT SUMMARIZATION

A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portal

ACL 2020 complementizer/wcep-mds-dataset

Multi-document summarization (MDS) aims to compress the content in large document collections into short summaries and has important applications in story clustering for newsfeeds, presentation of search results, and timeline generation.

DOCUMENT SUMMARIZATION MULTI-DOCUMENT SUMMARIZATION