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Automated Justification Production for Claim Veracity in Fact Checking: A Survey on Architectures and Approaches

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arxiv 2407.12853 v1 pith:QPLRVXGF submitted 2024-07-09 cs.CL cs.AIcs.IRcs.LG

Islam Eldifrawi , Shengrui Wang , Amine Trabelsi This is my paper · ORCID
classification cs.CLcs.AIcs.IRcs.LG
keywords automatedclaimanalysisfact-checkingmethodologiesresearchveracityaccuracy
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Towards Automated Fact-Checking of Real-World Claims: Exploring Task Formulation and Assessment with LLMs

    cs.CL 2025-02 conditional novelty 5.0 of 10

    In a benchmark of 17,856 PolitiFact claims, larger Llama-3 models and retrieved web evidence improve automated fact-checking accuracy and justification quality, though fine-grained labels remain difficult.

  2. AI4Research: A Survey of Artificial Intelligence for Scientific Research

    cs.CL 2025-07 conditional novelty 4.0 of 10

    A survey that organizes AI-for-research work into five tasks, comprehension, survey, discovery, writing, and peer review, and compiles associated tools and benchmarks.

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