mlsanityData to 7 Oct 2026

DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning

arXiv 1809.06416 ↗First posted 17 Sep 2018cs.CL cs.LGcited by 100

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Abstract (arXiv)

Misinformation such as fake news is one of the big challenges of our society. Research on automated fact-checking has proposed methods based on supervised learning, but these approaches do not consider external evidence apart from labeled training instances. Recent approaches counter this deficit by considering external sources related to a claim. However, these methods require substantial feature modeling and rich lexicons. This paper overcomes these limitations of prior work with an end-to-end model for evidence-aware credibility assessment of arbitrary textual claims, without any human intervention. It presents a neural network model that judiciously aggregates signals from external evidence articles, the language of these articles and the trustworthiness of their sources. It also derives informative features for generating user-comprehensible explanations that makes the neural network predictions transparent to the end-user. Experiments with four datasets and ablation studies show the strength of our method.

Key facts. Cited by 100 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Sep 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 19; 2022: 16; 2023: 13; 2024: 22; 2025: 14; 2026: 16.

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  1. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  2. 2021A Survey on Automated Fact-Checkingcited by 376
  3. 2021Get Your Vitamin C! Robust Fact Verification with Contrastive Evidencecited by 222
  4. 2023Complex Claim Verification with Evidence Retrieved in the Wildcited by 110
  5. 2023Towards LLM-based Fact Verification on News Claims with a Hierarchical Step-by-Step Prompting Methodcited by 97
  6. 2021Open-Domain, Content-based, Multi-modal Fact-checking of Out-of-Context Images via Online Resourcescited by 71
  7. 2023Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detectioncited by 69
  8. 2022Generating Literal and Implied Subquestions to Fact-check Complex Claimscited by 66
  9. 2021Towards Few-Shot Fact-Checking via Perplexitycited by 63
  10. 2021ProoFVer: Natural Logic Theorem Proving for Fact Verificationcited by 52
  11. 2023Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrongcited by 51
  12. 2024Explainable Fake News Detection With Large Language Model via Defense Among Competing Wisdomcited by 49
38 more
  1. 2022Generalizing to the Future: Mitigating Entity Bias in Fake News Detectioncited by 38
  2. 2023FactLLaMA: Optimizing Instruction-Following Language Models with External Knowledge for Automated Fact-Checkingcited by 37
  3. 2023Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language Modelscited by 37
  4. 2022Zoom Out and Observe: News Environment Perception for Fake News Detectioncited by 34
  5. 2022Memory-Guided Multi-View Multi-Domain Fake News Detectioncited by 31
  6. 2022Evidence-aware Fake News Detection with Graph Neural Networkscited by 30
  7. 2022CoVERT: A Corpus of Fact-checked Biomedical COVID-19 Tweetscited by 29
  8. 2024JustiLM: Few-shot Justification Generation for Explainable Fact-Checking of Real-world Claimscited by 29
  9. 2025Show Me the Work: Fact-Checkers' Requirements for Explainable Automated Fact-Checkingcited by 29
  10. 2024Exploring the Deceptive Power of LLM-Generated Fake News: A Study of Real-World Detection Challengescited by 28
  11. 2021Integrating Pattern- and Fact-based Fake News Detection via Model Preference Learningcited by 25
  12. 2023Benchmarking the Generation of Fact Checking Explanationscited by 25
  13. 2024QuanTemp: A real-world open-domain benchmark for fact-checking numerical claimscited by 22
  14. 2021Multimodal Emergent Fake News Detection via Meta Neural Process Networkscited by 21
  15. 2022An Empirical Study on Explanations in Out-of-Domain Settingscited by 21
  16. 2022ProtoTEx: Explaining Model Decisions with Prototype Tensorscited by 21
  17. 2021Overview of the CLEF-2019 CheckThat!: Automatic Identification and Verification of Claimscited by 18
  18. 2021Hierarchical Multi-head Attentive Network for Evidence-aware Fake News Detectioncited by 17
  19. 2021Article Reranking by Memory-Enhanced Key Sentence Matching for Detecting Previously Fact-Checked Claimscited by 16
  20. 2023FakeGPT: Fake News Generation, Explanation and Detection of Large Language Modelscited by 16
  21. 2024Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectorscited by 16
  22. 2022Contrastive Domain Adaptation for Early Misinformation Detection: A Case Study on COVID-19cited by 15
  23. 2022Exploring Faithful Rationale for Multi-hop Fact Verification via Salience-Aware Graph Learningcited by 15
  24. 2024Automated Justification Production for Claim Veracity in Fact Checking: A Survey on Architectures and Approachescited by 15
  25. 2024Reinforcement Retrieval Leveraging Fine-grained Feedback for Fact Checking News Claims with Black-Box LLMcited by 14
  26. 2021Misinformation Detection on YouTube Using Video Captionscited by 12
  27. 2022Claim-Dissector: An Interpretable Fact-Checking System with Joint Re-ranking and Veracity Predictioncited by 12
  28. 2022A Coarse-to-fine Cascaded Evidence-Distillation Neural Network for Explainable Fake News Detectioncited by 12
  29. 2024Large Language Model Agent for Fake News Detectioncited by 12
  30. 2021Dataset of Fake News Detection and Fact Verification: A Surveycited by 11
  31. 2022Fact-Saboteurs: A Taxonomy of Evidence Manipulation Attacks against Fact-Verification Systemscited by 11
  32. 2021On Unifying Misinformation Detectioncited by 10
  33. 2021Unified Dual-view Cognitive Model for Interpretable Claim Verificationcited by 10
  34. 2023Countering Misinformation via Emotional Response Generationcited by 9
  35. 2023QA-NatVer: Question Answering for Natural Logic-based Fact Verificationcited by 8
  36. 2024Credible, Unreliable or Leaked?: Evidence Verification for Enhanced Automated Fact-checkingcited by 8
  37. 2021Automatic Fake News Detection: Are Models Learning to Reason?cited by 7
  38. 2022Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networkscited by 7

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