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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 51–100 of 359 papers

TitleStatusHype
PDSum: Prototype-driven Continuous Summarization of Evolving Multi-document Sets StreamCode0
Pre-training Meets Clustering: A Hybrid Extractive Multi-document Summarization ModelCode0
Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical ModelCode0
Ask, Retrieve, Summarize: A Modular Pipeline for Scientific Literature SummarizationCode0
Multi-News+: Cost-efficient Dataset Cleansing via LLM-based Data AnnotationCode0
Abstractive Multi-Document Summarization via Joint Learning with Single-Document SummarizationCode0
DESCGEN: A Distantly Supervised Datasetfor Generating Entity DescriptionsCode0
Read what you need: Controllable Aspect-based Opinion Summarization of Tourist ReviewsCode0
Adapting the Neural Encoder-Decoder Framework from Single to Multi-Document SummarizationCode0
SgSum: Transforming Multi-document Summarization into Sub-graph SelectionCode0
MiRANews: Dataset and Benchmarks for Multi-Resource-Assisted News SummarizationCode0
Modeling Endorsement for Multi-Document Abstractive SummarizationCode0
Multi-Document Summarization with Centroid-Based PretrainingCode0
Leveraging Graph to Improve Abstractive Multi-Document SummarizationCode0
Coverage-based Fairness in Multi-document SummarizationCode0
Improving Fairness of Large Language Models in Multi-document SummarizationCode0
How "Multi" is Multi-Document Summarization?Code0
A Hierarchical Encoding-Decoding Scheme for Abstractive Multi-document SummarizationCode0
Hierarchical Transformers for Multi-Document SummarizationCode0
MDSWriter: Annotation Tool for Creating High-Quality Multi-Document Summarization CorporaCode0
Non-Parametric Memory Guidance for Multi-Document SummarizationCode0
GLIMMER: Incorporating Graph and Lexical Features in Unsupervised Multi-Document SummarizationCode0
Generating a Structured Summary of Numerous Academic Papers: Dataset and MethodCode0
Generating Wikipedia by Summarizing Long SequencesCode0
GLIMPSE: Pragmatically Informative Multi-Document Summarization for Scholarly ReviewsCode0
Clustering Sentences with Density Peaks for Multi-document SummarizationCode0
GenerationPrograms: Fine-grained Attribution with Executable ProgramsCode0
Compressed Heterogeneous Graph for Abstractive Multi-Document SummarizationCode0
Flight of the PEGASUS? Comparing Transformers on Few-shot and Zero-shot Multi-document Abstractive SummarizationCode0
From Single to Multi: How LLMs Hallucinate in Multi-Document SummarizationCode0
A General Optimization Framework for Multi-Document Summarization Using Genetic Algorithms and Swarm IntelligenceCode0
Corpora Evaluation and System Bias Detection in Multi-document SummarizationCode0
Centroid-based Text Summarization through Compositionality of Word EmbeddingsCode0
CQASUMM: Building References for Community Question Answering Summarization CorporaCode0
Fast Concept Mention Grouping for Concept Map-based Multi-Document SummarizationCode0
GlobeSumm: A Challenging Benchmark Towards Unifying Multi-lingual, Cross-lingual and Multi-document News SummarizationCode0
Extending Multi-Document Summarization Evaluation to the Interactive SettingCode0
Estimating Optimal Context Length for Hybrid Retrieval-augmented Multi-document SummarizationCode0
Extending Multi-Text Sentence Fusion Resources via Pyramid AnnotationsCode0
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
Extractive Multi-document Summarization using K-means, Centroid-based Method, MMR, and Sentence PositionCode0
Disentangling Specificity for Abstractive Multi-document SummarizationCode0
AllSummarizer system at MultiLing 2015: Multilingual single and multi-document summarizationCode0
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
OpenAsp: A Benchmark for Multi-document Open Aspect-based SummarizationCode0
Beyond Generic Summarization: A Multi-faceted Hierarchical Summarization Corpus of Large Heterogeneous DataCode0
An Extractive-Abstractive Approach for Multi-document Summarization of Scientific Articles for Literature ReviewCode0
ELSKE: Efficient Large-Scale Keyphrase ExtractionCode0
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