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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 1–50 of 359 papers

TitleStatusHype
GenerationPrograms: Fine-grained Attribution with Executable ProgramsCode0
Improving Fairness of Large Language Models in Multi-document SummarizationCode0
Ask, Retrieve, Summarize: A Modular Pipeline for Scientific Literature SummarizationCode0
A Unified Retrieval Framework with Document Ranking and EDU Filtering for Multi-document Summarization—0
Estimating Optimal Context Length for Hybrid Retrieval-augmented Multi-document SummarizationCode0
Can one size fit all?: Measuring Failure in Multi-Document Summarization Domain Transfer—0
Multi2: Multi-Agent Test-Time Scalable Framework for Multi-Document Processing—0
LAG: LLM agents for Leaderboard Auto Generation on Demanding—0
LM Agents for Coordinating Multi-User Information Gathering—0
Scaling Multi-Document Event Summarization: Evaluating Compression vs. Full-Text ApproachesCode0
EventSum: A Large-Scale Event-Centric Summarization Dataset for Chinese Multi-News Documents—0
Coverage-based Fairness in Multi-document SummarizationCode0
Fair Summarization: Bridging Quality and Diversity in Extractive SummariesCode0
From Single to Multi: How LLMs Hallucinate in Multi-Document SummarizationCode0
GlobeSumm: A Challenging Benchmark Towards Unifying Multi-lingual, Cross-lingual and Multi-document News SummarizationCode0
Leveraging Long-Context Large Language Models for Multi-Document Understanding and Summarization in Enterprise Applications—0
BERT-VBD: Vietnamese Multi-Document Summarization Framework—0
GLIMMER: Incorporating Graph and Lexical Features in Unsupervised Multi-Document SummarizationCode0
SumRecom: A Personalized Summarization Approach by Learning from Users' Feedback—0
Rethinking Transformer-based Multi-document Summarization: An Empirical Investigation—0
LightPAL: Lightweight Passage Retrieval for Open Domain Multi-Document Summarization—0
GLIMPSE: Pragmatically Informative Multi-Document Summarization for Scholarly ReviewsCode0
The Power of Summary-Source AlignmentsCode0
Text Generation: A Systematic Literature Review of Tasks, Evaluation, and ChallengesCode0
Which Information Matters? Dissecting Human-written Multi-document Summaries with Partial Information DecompositionCode0
Disentangling Specificity for Abstractive Multi-document SummarizationCode0
OARelatedWork: A Large-Scale Dataset of Related Work Sections with Full-texts from Open Access SourcesCode0
Understanding Position Bias Effects on Fairness in Social Multi-Document Summarization—0
Multi-News+: Cost-efficient Dataset Cleansing via LLM-based Data AnnotationCode0
Attribute First, then Generate: Locally-attributable Grounded Text GenerationCode1
NewsQs: Multi-Source Question Generation for the Inquiring Mind—0
SKT5SciSumm -- Revisiting Extractive-Generative Approach for Multi-Document Scientific Summarization—0
Benchmarking LLMs on the Semantic Overlap Summarization Task—0
Shaping Political Discourse using multi-source News SummarizationCode0
OpenAsp: A Benchmark for Multi-document Open Aspect-based SummarizationCode0
Supervising the Centroid Baseline for Extractive Multi-Document SummarizationCode0
Overview of the VLSP 2022 -- Abmusu Shared Task: A Data Challenge for Vietnamese Abstractive Multi-document Summarization—0
PELMS: Pre-training for Effective Low-Shot Multi-Document SummarizationCode0
Non-Parametric Memory Guidance for Multi-Document SummarizationCode0
Mitigating Framing Bias with Polarity Minimization Loss—0
LLM Based Multi-Document Summarization Exploiting Main-Event Biased Monotone Submodular Content Extraction—0
Controllable Multi-document Summarization: Coverage & Coherence Intuitive Policy with Large Language Model Based Rewards—0
Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News ArticlesCode1
ODSum: New Benchmarks for Open Domain Multi-Document SummarizationCode1
Multi-document Summarization: A Comparative Evaluation—0
Unsupervised Multi-document Summarization with Holistic Inference—0
Absformer: Transformer-based Model for Unsupervised Multi-Document Abstractive Summarization—0
Pre-training Meets Clustering: A Hybrid Extractive Multi-document Summarization ModelCode0
Revisiting Sentence Union Generation as a Testbed for Text ConsolidationCode0
Automated Metrics for Medical Multi-Document Summarization Disagree with Human EvaluationsCode0
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