paper
A Training-Free Mixture-of-Agents Framework for Multi-Document Summarization using LLMs and Knowledge Graphs
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a-training-free-mixture-of-agents-framework-for-multi-document-summarization-using-llms-and-knowledge-graphs-7d200d6b·1 events·first seen 13d agoAliases: A Training-Free Mixture-of-Agents Framework for Multi-Document Summarization using LLMs and Knowledge Graphs
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Training-free mixture-of-agents framework combines LLMs and knowledge graphs for multi-document summarization
A new arXiv preprint proposes a training-free multi-agent framework for multi-document summarization (MDS) that decomposes the task into specialized agents for extractive selection, knowledge-aware abstraction, and iterative refinement, unified via a multi-perspective consistency mechanism. The system integrates LLMs with knowledge graphs without task-specific fine-tuning. Experiments across four datasets in English and Vietnamese show state-of-the-art or competitive performance, with the authors emphasizing cross-domain and cross-lingual generalization.