mlsanityData to 7 Oct 2026

Towards LLM-based Fact Verification on News Claims with a Hierarchical Step-by-Step Prompting Method

arXiv 2310.00305 ↗First posted 30 Sep 2023cs.CLcited by 97

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Abstract (arXiv)

While large pre-trained language models (LLMs) have shown their impressive capabilities in various NLP tasks, they are still under-explored in the misinformation domain. In this paper, we examine LLMs with in-context learning (ICL) for news claim verification, and find that only with 4-shot demonstration examples, the performance of several prompting methods can be comparable with previous supervised models. To further boost performance, we introduce a Hierarchical Step-by-Step (HiSS) prompting method which directs LLMs to separate a claim into several subclaims and then verify each of them via multiple questions-answering steps progressively. Experiment results on two public misinformation datasets show that HiSS prompting outperforms state-of-the-art fully-supervised approach and strong few-shot ICL-enabled baselines.

Key facts. Cited by 97 papers in the map (data through 7 Oct 2026). Builds on 31 of its 51 references that are in the map. First posted on arXiv 30 Sep 2023.

Builds on

31 of 51 references.

References · 31

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  4. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  5. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  6. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,686
  7. 2019The Curious Case of Neural Text Degenerationcited by 2,881
  8. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  9. 2022Least-to-Most Prompting Enables Complex Reasoning in Large Language Modelscited by 1,397
  10. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,362
  11. 2023PaLM 2 Technical Reportcited by 1,154
  12. 2022Measuring and Narrowing the Compositionality Gap in Language Modelscited by 1,054
19 more
  1. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 888
  2. 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 695
  3. 2023Active Retrieval Augmented Generationcited by 506
  4. 2017"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detectioncited by 361
  5. 2020Explainable Automated Fact-Checking for Public Health Claimscited by 209
  6. 2020Generating Fact Checking Explanationscited by 132
  7. 2020GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Mediacited by 108
  8. 2018DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learningcited by 100
  9. 2023The science of fake newscited by 94
  10. 2021Towards Few-Shot Fact-Checking via Perplexitycited by 63
  11. 2019BERT for Evidence Retrieval and Claim Verificationcited by 57
  12. 2020Language Models as Fact Checkers?cited by 51
  13. 2020Generating Fact Checking Briefscited by 50
  14. 2021Embracing Domain Differences in Fake News: Cross-domain Fake News Detection using Multi-modal Datacited by 50
  15. 2019XFake: Explainable Fake News Detector with Visualizationscited by 32
  16. 2021Towards Fine-Grained Reasoning for Fake News Detectioncited by 32
  17. 2022Varifocal Question Generation for Fact-checkingcited by 27
  18. 2021A Multi-Level Attention Model for Evidence-Based Fact Checkingcited by 13
  19. 2022A Coarse-to-fine Cascaded Evidence-Distillation Neural Network for Explainable Fake News Detectioncited by 12

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 37; 2025: 40; 2026: 17.

97 papers.

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  1. 2023A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Uglycited by 380
  2. 2024Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMscited by 94
  3. 2023Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attackscited by 69
  4. 2024MMFakeBench: A Mixed-Source Multimodal Misinformation Detection Benchmark for LVLMscited by 60
  5. 2024DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Expertscited by 42
  6. 2024Argumentative Large Language Models for Explainable and Contestable Claim Verificationcited by 36
  7. 2024Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Modelscited by 35
  8. 2025PrivaCI-Bench: Evaluating Privacy with Contextual Integrity and Legal Compliancecited by 34
  9. 2024JustiLM: Few-shot Justification Generation for Explainable Fact-Checking of Real-world Claimscited by 29
  10. 2024RAGAR, Your Falsehood Radar: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Modelscited by 27
  11. 2024Retrieval Augmented Fact Verification by Synthesizing Contrastive Argumentscited by 25
  12. 2024Evidence-backed Fact Checking using RAG and Few-Shot In-Context Learning with LLMscited by 23
38 more
  1. 2024Claim Verification in the Age of Large Language Models: A Surveycited by 23
  2. 2024Deductive Closure Training of Language Models for Coherence, Accuracy, and Updatabilitycited by 22
  3. 2024Can We Trust LLMs? Mitigate Overconfidence Bias in LLMs through Knowledge Transfercited by 19
  4. 2024Generative Large Language Models in Automated Fact-Checking: A Surveycited by 19
  5. 2024Can LLMs Improve Multimodal Fact-Checking by Asking Relevant Questions?cited by 17
  6. 2024Reinforcement Retrieval Leveraging Fine-grained Feedback for Fact Checking News Claims with Black-Box LLMcited by 14
  7. 2024MCQG-SRefine: Multiple Choice Question Generation and Evaluation with Iterative Self-Critique, Correction, and Comparison Feedbackcited by 14
  8. 2024Web Retrieval Agents for Evidence-Based Misinformation Detectioncited by 13
  9. 2025Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Modelscited by 13
  10. 2024An Examination on the Effectiveness of Divide-and-Conquer Prompting in Large Language Modelscited by 12
  11. 2024Large Language Model Agent for Fake News Detectioncited by 12
  12. 2024Towards Collaborative Intelligence: Propagating Intentions and Reasoning for Multi-Agent Coordination with Large Language Modelscited by 10
  13. 2024A Guide to Misinformation Detection Data and Evaluationcited by 10
  14. 2025Beyond the Crowd: LLM-Augmented Community Notes for Governing Health Misinformationcited by 10
  15. 2024Comparing GPT-4 and Open-Source Language Models in Misinformation Mitigationcited by 9
  16. 2024Privacy-preserved LLM Cascade via CoT-enhanced Policy Learningcited by 8
  17. 2024'Quis custodiet ipsos custodes?' Who will watch the watchmen? On Detecting AI-generated peer-reviewscited by 8
  18. 2025From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systemscited by 8
  19. 2025Retrieval- and Argumentation-Enhanced Multi-Agent LLMs for Judgmental Forecasting (Extended Version with Supplementary Material)cited by 8
  20. 2025Is LLMs Hallucination Usable? LLM-based Negative Reasoning for Fake News Detectioncited by 7
  21. 2025EarthSE: A Benchmark for Evaluating Earth Scientific Exploration Capability of LLMscited by 7
  22. 2025The Missing Parts: Augmenting Fact Verification with Half-Truth Detectioncited by 7
  23. 2025FaStfact: Faster, Stronger Long-Form Factuality Evaluations in LLMscited by 7
  24. 2026Robust Fake News Detection using Large Language Models under Adversarial Sentiment Attackscited by 7
  25. 2024VeraCT Scan: Retrieval-Augmented Fake News Detection with Justifiable Reasoningcited by 6
  26. 2025A Multi-Agent Framework with Automated Decision Rule Optimization for Cross-Domain Misinformation Detectioncited by 6
  27. 2025CMIE: Combining MLLM Insights with External Evidence for Explainable Out-of-Context Misinformation Detectioncited by 6
  28. 2023XplainLLM: A Knowledge-Augmented Dataset for Reliable Grounded Explanations in LLMscited by 5
  29. 2024A Survey on Neural Question Generation: Methods, Applications, and Prospectscited by 5
  30. 2024Reinforcement Tuning for Detecting Stances and Debunking Rumors Jointly with Large Language Modelscited by 5
  31. 2025Reasoning-CV: Fine-tuning Powerful Reasoning LLMs for Knowledge-Assisted Claim Verificationcited by 5
  32. 2025Verify-in-the-Graph: Entity Disambiguation Enhancement for Complex Claim Verification with Interactive Graph Representationcited by 5
  33. 2025A Survey on Proactive Defense Strategies Against Misinformation in Large Language Modelscited by 5
  34. 2025A Graph-based Verification Framework for Fact-Checkingcited by 4
  35. 2025MAD-Fact: A Multi-Agent Debate Framework for Long-Form Factuality Evaluation in LLMscited by 4
  36. 2024MMIDR: Teaching Large Language Model to Interpret Multimodal Misinformation via Knowledge Distillationcited by 3
  37. 2024Zero-Shot Learning and Key Points Are All You Need for Automated Fact-Checkingcited by 3
  38. 2024Take It Easy: Label-Adaptive Self-Rationalization for Fact Verification and Explanation Generationcited by 3

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