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Automated Fact Checking: Task formulations, methods and future directions

arXiv 1806.07687 ↗First posted 20 Jun 2018cs.CLcited by 96

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Abstract (arXiv)

The recently increased focus on misinformation has stimulated research in fact checking, the task of assessing the truthfulness of a claim. Research in automating this task has been conducted in a variety of disciplines including natural language processing, machine learning, knowledge representation, databases, and journalism. While there has been substantial progress, relevant papers and articles have been published in research communities that are often unaware of each other and use inconsistent terminology, thus impeding understanding and further progress. In this paper we survey automated fact checking research stemming from natural language processing and related disciplines, unifying the task formulations and methodologies across papers and authors. Furthermore, we highlight the use of evidence as an important distinguishing factor among them cutting across task formulations and methods. We conclude with proposing avenues for future NLP research on automated fact checking.

Key facts. Cited by 96 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Jun 2018.

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Citing papers per year: 2021: 32; 2022: 17; 2023: 10; 2024: 15; 2025: 10; 2026: 12.

96 papers.

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  1. 2021A Survey on Automated Fact-Checkingcited by 378
  2. 2021Measuring Attribution in Natural Language Generation Modelscited by 256
  3. 2021Mind the Gap: Assessing Temporal Generalization in Neural Language Modelscited by 230
  4. 2021Get Your Vitamin C! Robust Fact Verification with Contrastive Evidencecited by 225
  5. 2021FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured informationcited by 167
  6. 2024Fine-grained Hallucination Detection and Editing for Language Modelscited by 149
  7. 2023Fact-Checking Complex Claims with Program-Guided Reasoningcited by 146
  8. 2021Automated Fact-Checking for Assisting Human Fact-Checkerscited by 144
  9. 2021A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generationcited by 138
  10. 2021Q2: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answeringcited by 132
  11. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  12. 2021Open-Domain, Content-based, Multi-modal Fact-checking of Out-of-Context Images via Online Resourcescited by 71
38 more
  1. 2022Detecting and Understanding Harmful Memes: A Surveycited by 58
  2. 2021Automated Fact-Checking: A Surveycited by 55
  3. 2023Scientific Fact-Checking: A Survey of Resources and Approachescited by 54
  4. 2023Multimodal Automated Fact-Checking: A Surveycited by 53
  5. 2023Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrongcited by 51
  6. 2021A Survey on Multimodal Disinformation Detectioncited by 47
  7. 2022Missing Counter-Evidence Renders NLP Fact-Checking Unrealistic for Misinformationcited by 45
  8. 2022Synthetic Disinformation Attacks on Automated Fact Verification Systemscited by 44
  9. 2021AmbiFC: Fact-Checking Ambiguous Claims with Evidencecited by 38
  10. 2022CoVERT: A Corpus of Fact-checked Biomedical COVID-19 Tweetscited by 29
  11. 2025Worse than Zero-shot? A Fact-Checking Dataset for Evaluating the Robustness of RAG Against Misleading Retrievalscited by 28
  12. 2024Evidence-backed Fact Checking using RAG and Few-Shot In-Context Learning with LLMscited by 24
  13. 2024QuanTemp: A real-world open-domain benchmark for fact-checking numerical claimscited by 23
  14. 2023An Overview on Language Models: Recent Developments and Outlookcited by 22
  15. 2021A Survey on Predicting the Factuality and the Bias of News Mediacited by 20
  16. 2021Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Documentcited by 19
  17. 2023The Intended Uses of Automated Fact-Checking Artefacts: Why, How and Whocited by 19
  18. 2024Generative Large Language Models in Automated Fact-Checking: A Surveycited by 19
  19. 2021The Role of Context in Detecting Previously Fact-Checked Claimscited by 17
  20. 2022Crowdsourced Fact-Checking at Twitter: How Does the Crowd Compare With Experts?cited by 16
  21. 2022Matching Tweets With Applicable Fact-Checks Across Languagescited by 15
  22. 2024Automated Justification Production for Claim Veracity in Fact Checking: A Survey on Architectures and Approachescited by 15
  23. 2021Transformer based Automatic COVID-19 Fake News Detection Systemcited by 14
  24. 2021Findings of the NLP4IF-2021 Shared Tasks on Fighting the COVID-19 Infodemic and Censorship Detectioncited by 14
  25. 2021Misinformation Detection on YouTube Using Video Captionscited by 12
  26. 2022Fact-Saboteurs: A Taxonomy of Evidence Manipulation Attacks against Fact-Verification Systemscited by 12
  27. 2024Piecing It All Together: Verifying Multi-Hop Multimodal Claimscited by 12
  28. 2021Dataset of Fake News Detection and Fact Verification: A Surveycited by 11
  29. 2022Improving Wikipedia Verifiability with AIcited by 11
  30. 2021FacTeR-Check: Semi-automated fact-checking through Semantic Similarity and Natural Language Inferencecited by 10
  31. 2022Evaluation of Fake News Detection with Knowledge-Enhanced Language Modelscited by 9
  32. 2021Extractive and Abstractive Explanations for Fact-Checking and Evaluation of Newscited by 8
  33. 2023Identifying Conspiracy Theories News based on Event Relation Graphcited by 8
  34. 2023Are Large Language Models Good Fact Checkers: A Preliminary Studycited by 8
  35. 2025BiDeV: Bilateral Defusing Verification for Complex Claim Fact-Checkingcited by 8
  36. 2021Automatic Fake News Detection: Are Models Learning to Reason?cited by 7
  37. 2022Entity-based Claim Representation Improves Fact-Checking of Medical Content in Tweetscited by 7
  38. 2023Logic Against Bias: Textual Entailment Mitigates Stereotypical Sentence Reasoningcited by 7

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