mlsanityData to 7 Oct 2026

Generating Fact Checking Explanations

arXiv 2004.05773 ↗First posted 13 Apr 2020cs.CL cs.AI cs.LGcited by 132

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Abstract (arXiv)

Most existing work on automated fact checking is concerned with predicting the veracity of claims based on metadata, social network spread, language used in claims, and, more recently, evidence supporting or denying claims. A crucial piece of the puzzle that is still missing is to understand how to automate the most elaborate part of the process -- generating justifications for verdicts on claims. This paper provides the first study of how these explanations can be generated automatically based on available claim context, and how this task can be modelled jointly with veracity prediction. Our results indicate that optimising both objectives at the same time, rather than training them separately, improves the performance of a fact checking system. The results of a manual evaluation further suggest that the informativeness, coverage and overall quality of the generated explanations are also improved in the multi-task model.

Key facts. Cited by 132 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Apr 2020.

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Citing papers per year: 2021: 26; 2022: 13; 2023: 25; 2024: 29; 2025: 25; 2026: 14.

132 papers.

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  1. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,582
  2. 2021A Survey on Automated Fact-Checkingcited by 376
  3. 2022From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AIcited by 299
  4. 2021Get Your Vitamin C! Robust Fact Verification with Contrastive Evidencecited by 222
  5. 2023Fact-Checking Complex Claims with Program-Guided Reasoningcited by 146
  6. 2021Annotating and Modeling Fine-grained Factuality in Summarizationcited by 131
  7. 2021Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyondcited by 116
  8. 2023Complex Claim Verification with Evidence Retrieved in the Wildcited by 110
  9. 2023Faithfulness Tests for Natural Language Explanationscited by 107
  10. 2022End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Modelscited by 105
  11. 2023Towards LLM-based Fact Verification on News Claims with a Hierarchical Step-by-Step Prompting Methodcited by 97
  12. 2021QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehensioncited by 91
38 more
  1. 2023Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkerscited by 86
  2. 2021e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Taskscited by 84
  3. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  4. 2022Generating Literal and Implied Subquestions to Fact-check Complex Claimscited by 66
  5. 2023FactKG: Fact Verification via Reasoning on Knowledge Graphscited by 57
  6. 2025Evaluating LLM-based Agents for Multi-Turn Conversations: A Surveycited by 56
  7. 2023HAGRID: A Human-LLM Collaborative Dataset for Generative Information-Seeking with Attributioncited by 55
  8. 2021ProoFVer: Natural Logic Theorem Proving for Fact Verificationcited by 52
  9. 2023Multimodal Automated Fact-Checking: A Surveycited by 51
  10. 2024Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debatecited by 48
  11. 2021A Survey on Multimodal Disinformation Detectioncited by 47
  12. 2024CiteME: Can Language Models Accurately Cite Scientific Claims?cited by 45
  13. 2024DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Expertscited by 42
  14. 2023FactLLaMA: Optimizing Instruction-Following Language Models with External Knowledge for Automated Fact-Checkingcited by 37
  15. 2023Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language Modelscited by 37
  16. 2023EX-FEVER: A Dataset for Multi-hop Explainable Fact Verificationcited by 36
  17. 2021Is Sparse Attention more Interpretable?cited by 31
  18. 2024JustiLM: Few-shot Justification Generation for Explainable Fact-Checking of Real-world Claimscited by 29
  19. 2025Show Me the Work: Fact-Checkers' Requirements for Explainable Automated Fact-Checkingcited by 29
  20. 2021COSMOS: Catching Out-of-Context Misinformation with Self-Supervised Learningcited by 26
  21. 2023Benchmarking the Generation of Fact Checking Explanationscited by 25
  22. 2023Fin-Fact: A Benchmark Dataset for Multimodal Financial Fact Checking and Explanation Generationcited by 25
  23. 2021Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanationscited by 24
  24. 2025Hallucination Detection in Large Language Models with Metamorphic Relationscited by 24
  25. 2023Rationalization for Explainable NLP: A Surveycited by 22
  26. 2022ProtoTEx: Explaining Model Decisions with Prototype Tensorscited by 21
  27. 2022AdapLeR: Speeding up Inference by Adaptive Length Reductioncited by 19
  28. 2024FinDVer: Explainable Claim Verification over Long and Hybrid-Content Financial Documentscited by 19
  29. 2025FACT-AUDIT: An Adaptive Multi-Agent Framework for Dynamic Fact-Checking Evaluation of Large Language Modelscited by 19
  30. 2021Explainable Fact-checking through Question Answeringcited by 16
  31. 2022Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanationcited by 16
  32. 2021Generating Fluent Fact Checking Explanations with Unsupervised Post-Editingcited by 15
  33. 2022Exploring Faithful Rationale for Multi-hop Fact Verification via Salience-Aware Graph Learningcited by 15
  34. 2024Automated Justification Production for Claim Veracity in Fact Checking: A Survey on Architectures and Approachescited by 15
  35. 2022A Coarse-to-fine Cascaded Evidence-Distillation Neural Network for Explainable Fake News Detectioncited by 12
  36. 2022Fact-Saboteurs: A Taxonomy of Evidence Manipulation Attacks against Fact-Verification Systemscited by 11
  37. 2025Explainability in Practice: A Survey of Explainable NLP Across Various Domainscited by 11
  38. 2024FACTOID: FACtual enTailment fOr hallucInation Detectioncited by 10

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