mlsanityData to 7 Oct 2026

"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection

arXiv 1705.00648 ↗First posted 1 May 2017cs.CL cs.CYcited by 361

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Abstract (arXiv)

Automatic fake news detection is a challenging problem in deception detection, and it has tremendous real-world political and social impacts. However, statistical approaches to combating fake news has been dramatically limited by the lack of labeled benchmark datasets. In this paper, we present liar: a new, publicly available dataset for fake news detection. We collected a decade-long, 12.8K manually labeled short statements in various contexts from PolitiFact.com, which provides detailed analysis report and links to source documents for each case. This dataset can be used for fact-checking research as well. Notably, this new dataset is an order of magnitude larger than previously largest public fake news datasets of similar type. Empirically, we investigate automatic fake news detection based on surface-level linguistic patterns. We have designed a novel, hybrid convolutional neural network to integrate meta-data with text. We show that this hybrid approach can improve a text-only deep learning model.

Key facts. Cited by 361 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 May 2017.

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Citing papers per year: 2021: 66; 2022: 59; 2023: 57; 2024: 61; 2025: 67; 2026: 51.

361 papers.

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  1. 2023CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquingcited by 751
  2. 2023Automatic Prompt Optimization with "Gradient Descent" and Beam Searchcited by 628
  3. 2021MetaICL: Learning to Learn In Contextcited by 450
  4. 2021A Survey on Automated Fact-Checkingcited by 376
  5. 2022RARR: Researching and Revising What Language Models Say, Using Language Modelscited by 286
  6. 2023From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Modelscited by 257
  7. 2021Get Your Vitamin C! Robust Fact Verification with Contrastive Evidencecited by 222
  8. 2022Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Modelscited by 179
  9. 2021FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured informationcited by 166
  10. 2023Fact-Checking Complex Claims with Program-Guided Reasoningcited by 146
  11. 2024Fine-grained Hallucination Detection and Editing for Language Modelscited by 146
  12. 2023AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Webcited by 144
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  1. 2021CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLPcited by 142
  2. 2024Benchmark Data Contamination of Large Language Models: A Surveycited by 138
  3. 2021TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generationcited by 118
  4. 2023Complex Claim Verification with Evidence Retrieved in the Wildcited by 110
  5. 2022End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Modelscited by 105
  6. 2023Detecting and Grounding Multi-Modal Media Manipulationcited by 98
  7. 2023Towards LLM-based Fact Verification on News Claims with a Hierarchical Step-by-Step Prompting Methodcited by 97
  8. 2021X-FACT: A New Benchmark Dataset for Multilingual Fact Checkingcited by 90
  9. 2021CREAK: A Dataset for Commonsense Reasoning over Entity Knowledgecited by 88
  10. 2021User Preference-aware Fake News Detectioncited by 76
  11. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  12. 2022MDFEND: Multi-domain Fake News Detectioncited by 68
  13. 2022Generating Literal and Implied Subquestions to Fact-check Complex Claimscited by 66
  14. 2021DialFact: A Benchmark for Fact-Checking in Dialoguecited by 62
  15. 2025A Systematic Survey of Automatic Prompt Optimization Techniquescited by 61
  16. 2022MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Datasetcited by 59
  17. 2021Automated Fact-Checking: A Surveycited by 55
  18. 2023Detecting and Grounding Multi-Modal Media Manipulation and Beyondcited by 55
  19. 2023Deception Detection from Linguistic and Physiological Data Streams Using Bimodal Convolutional Neural Networkscited by 54
  20. 2022Missing Counter-Evidence Renders NLP Fact-Checking Unrealistic for Misinformationcited by 45
  21. 2023Towards Reliable Misinformation Mitigation: Generalization, Uncertainty, and GPT-4cited by 45
  22. 2021RAFT: A Real-World Few-Shot Text Classification Benchmarkcited by 44
  23. 2024DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Expertscited by 42
  24. 2023Pre-Training to Learn in Contextcited by 41
  25. 2022CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checkingcited by 37
  26. 2023FactLLaMA: Optimizing Instruction-Following Language Models with External Knowledge for Automated Fact-Checkingcited by 37
  27. 2025Self-Supervised Prompt Optimizationcited by 37
  28. 2023EX-FEVER: A Dataset for Multi-hop Explainable Fact Verificationcited by 36
  29. 2021Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learningcited by 35
  30. 2023Reading and Reasoning over Chart Images for Evidence-based Automated Fact-Checkingcited by 34
  31. 2023Open, Closed, or Small Language Models for Text Classification?cited by 34
  32. 2021Misinfo Reaction Frames: Reasoning about Readers' Reactions to News Headlinescited by 32
  33. 2022Evidence-aware Fake News Detection with Graph Neural Networkscited by 30
  34. 2022CoVERT: A Corpus of Fact-checked Biomedical COVID-19 Tweetscited by 29
  35. 2024JustiLM: Few-shot Justification Generation for Explainable Fact-Checking of Real-world Claimscited by 29
  36. 2024The Automated Verification of Textual Claims (AVeriTeC) Shared Taskcited by 29
  37. 2023PREFER: Prompt Ensemble Learning via Feedback-Reflect-Refinecited by 28
  38. 2025Worse than Zero-shot? A Fact-Checking Dataset for Evaluating the Robustness of RAG Against Misleading Retrievalscited by 27

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