Automated Justification Production for Claim Veracity in Fact Checking: A Survey on Architectures and Approaches
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Abstract (arXiv)
Automated Fact-Checking (AFC) is the automated verification of claim accuracy. AFC is crucial in discerning truth from misinformation, especially given the huge amounts of content are generated online daily. Current research focuses on predicting claim veracity through metadata analysis and language scrutiny, with an emphasis on justifying verdicts. This paper surveys recent methodologies, proposing a comprehensive taxonomy and presenting the evolution of research in that landscape. A comparative analysis of methodologies and future directions for improving fact-checking explainability are also discussed.
Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 47 of its 74 references that are in the map. First posted on arXiv 9 Jul 2024.
Builds on
47 of 74 references.
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Citing papers per year: 2025: 11; 2026: 4.
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- 2025ReportBench: Evaluating Deep Research Agents via Academic Survey Taskscited by 34
- 2025FACT-AUDIT: An Adaptive Multi-Agent Framework for Dynamic Fact-Checking Evaluation of Large Language Modelscited by 19
- 2025ADMIT: Few-shot Knowledge Poisoning Attacks on RAG-based Fact Checkingcited by 9
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- 2026SoK: Formal Methods for Fact-Checking and Information Integrity19 Sep 2026
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- 2026Contradiction to Consensus: Dual Perspective, Multi Source Retrieval Based Claim Verification with Source Level Disagreement using LLM21 Feb 2026
- 2026Can Deep Research Agents Retrieve and Organize? Evaluating the Synthesis Gap with Expert Taxonomies18 Jan 2026
- 2025COMMUNITYNOTES: A Dataset for Exploring the Helpfulness of Fact-Checking Explanations28 Oct 2025
- 2025ADMIT: Few-shot Knowledge Poisoning Attacks on RAG-based Fact Checking11 Oct 2025
- 2025The Psychology of Falsehood: A Human-Centric Survey of Misinformation Detection19 Sep 2025
- 2025Adversarial Attacks Against Automated Fact-Checking: A Survey10 Sep 2025
- 2025ReportBench: Evaluating Deep Research Agents via Academic Survey Tasks14 Aug 2025
- 2025Reasoning-CV: Fine-tuning Powerful Reasoning LLMs for Knowledge-Assisted Claim Verification18 May 2025
- 2025FinGrAct: A Framework for FINe-GRrained Evaluation of ACTionability in Explainable Automatic Fact-Checking7 Apr 2025
- 2025SciClaims: An End-to-End Generative System for Biomedical Claim Analysis24 Mar 2025
3 more
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- 2025FACT-AUDIT: An Adaptive Multi-Agent Framework for Dynamic Fact-Checking Evaluation of Large Language Models25 Feb 2025
- 2025Towards Automated Fact-Checking of Real-World Claims: Exploring Task Formulation and Assessment with LLMs13 Feb 2025
- 2025ReportBench: Evaluating Deep Research Agents via Academic Survey Taskscited by 34
- 2025FACT-AUDIT: An Adaptive Multi-Agent Framework for Dynamic Fact-Checking Evaluation of Large Language Modelscited by 19
- 2026Can Deep Research Agents Retrieve and Organize? Evaluating the Synthesis Gap with Expert Taxonomiescited by 3
- 2026Can Deep Research Agents Retrieve and Organize? Evaluating the Synthesis Gap with Expert Taxonomies18 Jan 2026
- 2025ReportBench: Evaluating Deep Research Agents via Academic Survey Tasks14 Aug 2025
- 2025FACT-AUDIT: An Adaptive Multi-Agent Framework for Dynamic Fact-Checking Evaluation of Large Language Models25 Feb 2025
- 2025From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systemscited by 8
- 2025Towards Automated Fact-Checking of Real-World Claims: Exploring Task Formulation and Assessment with LLMscited by 5
- 2025Adversarial Attacks Against Automated Fact-Checking: A Surveycited by 5
- 2025COMMUNITYNOTES: A Dataset for Exploring the Helpfulness of Fact-Checking Explanationscited by 5
- 2025SciClaims: An End-to-End Generative System for Biomedical Claim Analysiscited by 2
- 2025FinGrAct: A Framework for FINe-GRrained Evaluation of ACTionability in Explainable Automatic Fact-Checkingcited by 1
- 2025The Psychology of Falsehood: A Human-Centric Survey of Misinformation Detectioncited by 1
- 2026Contradiction to Consensus: Dual Perspective, Multi Source Retrieval Based Claim Verification with Source Level Disagreement using LLMcited by 1
- 2026Can temporal article-level credibility signals improve domain-level credibility prediction?cited by 0
- 2026SoK: Formal Methods for Fact-Checking and Information Integritycited by 0
- 2026SoK: Formal Methods for Fact-Checking and Information Integrity19 Sep 2026
- 2026Can temporal article-level credibility signals improve domain-level credibility prediction?6 Jul 2026
- 2026Contradiction to Consensus: Dual Perspective, Multi Source Retrieval Based Claim Verification with Source Level Disagreement using LLM21 Feb 2026
- 2025COMMUNITYNOTES: A Dataset for Exploring the Helpfulness of Fact-Checking Explanations28 Oct 2025
- 2025The Psychology of Falsehood: A Human-Centric Survey of Misinformation Detection19 Sep 2025
- 2025Adversarial Attacks Against Automated Fact-Checking: A Survey10 Sep 2025
- 2025FinGrAct: A Framework for FINe-GRrained Evaluation of ACTionability in Explainable Automatic Fact-Checking7 Apr 2025
- 2025SciClaims: An End-to-End Generative System for Biomedical Claim Analysis24 Mar 2025
- 2025From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systems3 Mar 2025
- 2025Towards Automated Fact-Checking of Real-World Claims: Exploring Task Formulation and Assessment with LLMs13 Feb 2025