mlsanityData to 7 Oct 2026

Self-Checker: Plug-and-Play Modules for Fact-Checking with Large Language Models

arXiv 2305.14623 ↗First posted 24 May 2023cs.CLcited by 31

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Abstract (arXiv)

Fact-checking is an essential task in NLP that is commonly utilized for validating the factual accuracy of claims. Prior work has mainly focused on fine-tuning pre-trained languages models on specific datasets, which can be computationally intensive and time-consuming. With the rapid development of large language models (LLMs), such as ChatGPT and GPT-3, researchers are now exploring their in-context learning capabilities for a wide range of tasks. In this paper, we aim to assess the capacity of LLMs for fact-checking by introducing Self-Checker, a framework comprising a set of plug-and-play modules that facilitate fact-checking by purely prompting LLMs in an almost zero-shot setting. This framework provides a fast and efficient way to construct fact-checking systems in low-resource environments. Empirical results demonstrate the potential of Self-Checker in utilizing LLMs for fact-checking. However, there is still significant room for improvement compared to SOTA fine-tuned models, which suggests that LLM adoption could be a promising approach for future fact-checking research.

Key facts. Cited by 31 papers in the map (data through 7 Oct 2026). Builds on 25 of its 41 references that are in the map. First posted on arXiv 24 May 2023.

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25 of 41 references.

References · 25

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  4. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,362
  5. 2023FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generationcited by 1,259
  6. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  7. 2019TabFact: A Large-scale Dataset for Table-based Fact Verificationcited by 425
  8. 2021A Survey on Automated Fact-Checkingcited by 376
  9. 2023Evaluating Verifiability in Generative Search Enginescited by 297
  10. 2021Get Your Vitamin C! Robust Fact Verification with Contrastive Evidencecited by 222
  11. 2016A Decomposable Attention Model for Natural Language Inferencecited by 214
  12. 2023Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Frameworkcited by 139
13 more
  1. 2023WiCE: Real-World Entailment for Claims in Wikipediacited by 118
  2. 2020INFOTABS: Inference on Tables as Semi-structured Datacited by 84
  3. 2019BERT for Evidence Retrieval and Claim Verificationcited by 57
  4. 2023FactKG: Fact Verification via Reasoning on Knowledge Graphscited by 57
  5. 2021Automated Fact-Checking: A Surveycited by 55
  6. 2021ProoFVer: Natural Logic Theorem Proving for Fact Verificationcited by 52
  7. 2021A Survey on Multimodal Disinformation Detectioncited by 47
  8. 2020Overview of CheckThat! 2020: Automatic Identification and Verification of Claims in Social Mediacited by 46
  9. 2020Evidence-based Factual Error Correctioncited by 44
  10. 2018Overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims. Task 1: Check-Worthinesscited by 41
  11. 2021FRUIT: Faithfully Reflecting Updated Information in Textcited by 39
  12. 2023Zero-shot Faithful Factual Error Correctioncited by 26
  13. 2023BEVERS: A General, Simple, and Performant Framework for Automatic Fact Verificationcited by 11

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Citing papers per year: 2023: 7; 2024: 11; 2025: 8; 2026: 5.

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  1. 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
  2. 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 695
  3. 2023Cognitive Mirage: A Review of Hallucinations in Large Language Modelscited by 83
  4. 2024DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Expertscited by 42
  5. 2024Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?cited by 40
  6. 2024Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Modelscited by 27
  7. 2024Claim Verification in the Age of Large Language Models: A Surveycited by 23
  8. 2024Pelican: Correcting Hallucination in Vision-LLMs via Claim Decomposition and Program of Thought Verificationcited by 17
  9. 2024Understanding the Effects of Iterative Prompting on Truthfulnesscited by 14
  10. 2023StrategyLLM: Large Language Models as Strategy Generators, Executors, Optimizers, and Evaluators for Problem Solvingcited by 13
  11. 2025Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Modelscited by 13
  12. 2023AutoHall: Automated Factuality Hallucination Dataset Generation for Large Language Modelscited by 10
19 more
  1. 2024Assessing the Reasoning Capabilities of LLMs in the context of Evidence-based Claim Verificationcited by 9
  2. 2025Orchestrating Agents and Data for Enterprise: A Blueprint Architecture for Compound AIcited by 9
  3. 2024Re-Ex: Revising after Explanation Reduces the Factual Errors in LLM Responsescited by 6
  4. 2024SELU: Self-Learning Embodied MLLMs in Unknown Environmentscited by 6
  5. 2025Evaluating open-source Large Language Models for automated fact-checkingcited by 6
  6. 2023Generating Explanations to Understand and Repair Embedding-based Entity Alignmentcited by 5
  7. 2023KGQuiz: Evaluating the Generalization of Encoded Knowledge in Large Language Modelscited by 4
  8. 2024Familiarity-Aware Evidence Compression for Retrieval-Augmented Generationcited by 4
  9. 2025MAD-Fact: A Multi-Agent Debate Framework for Long-Form Factuality Evaluation in LLMscited by 4
  10. 2025STRIVE: Structured Reasoning for Self-Improvement in Claim Verificationcited by 3
  11. 2024Mining the Explainability and Generalization: Fact Verification Based on Self-Instructioncited by 0
  12. 2025Towards Robust Fact-Checking: A Multi-Agent System with Advanced Evidence Retrievalcited by 0
  13. 2025Sample, Align, Synthesize: Graph-Based Response Synthesis with ConGrscited by 0
  14. 2025EmeraldMind: A Knowledge Graph-Augmented Framework for Greenwashing Detectioncited by 0
  15. 2026Fact-Checking with Large Language Models via Probabilistic Certainty and Consistencycited by 0
  16. 2026MERMAID: Memory-Enhanced Retrieval and Reasoning with Multi-Agent Iterative Knowledge Grounding for Veracity Assessmentcited by 0
  17. 2026The Alignment Bottleneck in Decomposition-Based Claim Verificationcited by 0
  18. 2026NTS-CoT: Mitigating Hallucinations in LLM-based News Timeline Summarization with Chain-of-Thought Reasoningcited by 0
  19. 2026Hallucinations in LLMs: A Lifecycle-Based Survey of Causes, Detection, Mitigation, and Preventioncited by 0