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News/A Graph-Enhanced Defense Framework for Explainable Fake News Detection with LLM
arxiv
PublishedApril 10, 2026 at 4:00 AM
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A Graph-Enhanced Defense Framework for Explainable Fake News Detection with LLM

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2604.06666v1 Announce Type: cross Abstract: Explainable fake news detection aims to assess the veracity of news claims while providing human-friendly explanations. Existing methods incorporating investigative journalism are often inefficient and struggle with breaking news. Recent advances in

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Discussion
Mentioned models
03
  • 01
    Large Language Models (LLMs)
  • 02
    Graph-Enhanced Defense Framework (G-Defense)
  • 03
    Retrieval-Augmented Generation (RAG)
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#explainability#fake-news-detection#natural-language-processing

No replies yet. Be first.

Mentioned models
03
  • 01
    Large Language Models (LLMs)
  • 02
    Graph-Enhanced Defense Framework (G-Defense)
  • 03
    Retrieval-Augmented Generation (RAG)
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#explainability#fake-news-detection#natural-language-processing

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arxivVeriEvolve: Evaluator-First Evolution for Tool-Using Agents1darxivTNODEV: Toolbox for Neural ODE Verification1d
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