mlsanityData to 14 Oct 2026

Complex Claim Verification with Evidence Retrieved in the Wild

arXiv 2305.11859 ↗First posted 19 May 2023cs.CLcited by 110

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Abstract (arXiv)

Evidence retrieval is a core part of automatic fact-checking. Prior work makes simplifying assumptions in retrieval that depart from real-world use cases: either no access to evidence, access to evidence curated by a human fact-checker, or access to evidence available long after the claim has been made. In this work, we present the first fully automated pipeline to check real-world claims by retrieving raw evidence from the web. We restrict our retriever to only search documents available prior to the claim's making, modeling the realistic scenario where an emerging claim needs to be checked. Our pipeline includes five components: claim decomposition, raw document retrieval, fine-grained evidence retrieval, claim-focused summarization, and veracity judgment. We conduct experiments on complex political claims in the ClaimDecomp dataset and show that the aggregated evidence produced by our pipeline improves veracity judgments. Human evaluation finds the evidence summary produced by our system is reliable (it does not hallucinate information) and relevant to answering key questions about a claim, suggesting that it can assist fact-checkers even when it cannot surface a complete evidence set.

Key facts. Cited by 110 papers in the map (data through 14 Oct 2026). Builds on 48 of its 68 references that are in the map. First posted on arXiv 19 May 2023.

Builds on

48 of 68 references.

References · 48

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2022Training language models to follow instructions with human feedbackcited by 15,971
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
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  11. 2022LaMDA: Language Models for Dialog Applicationscited by 1,220
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36 more
  1. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 792
  2. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  3. 2021Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategiescited by 743
  4. 2023In-Context Retrieval-Augmented Language Modelscited by 702
  5. 2023Benchmarking Large Language Models for News Summarizationcited by 445
  6. 2018The Web as a Knowledge-base for Answering Complex Questionscited by 410
  7. 2020Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performancecited by 399
  8. 2017"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detectioncited by 363
  9. 2022News Summarization and Evaluation in the Era of GPT-3cited by 327
  10. 2022RARR: Researching and Revising What Language Models Say, Using Language Modelscited by 287
  11. 2021Get Your Vitamin C! Robust Fact Verification with Contrastive Evidencecited by 225
  12. 2020HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verificationcited by 201
  13. 2019MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claimscited by 169
  14. 2022Improving Passage Retrieval with Zero-Shot Question Generationcited by 165
  15. 2017Automatic Detection of Fake Newscited by 145
  16. 2021Automated Fact-Checking for Assisting Human Fact-Checkerscited by 144
  17. 2022Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluationcited by 142
  18. 2020Generating Fact Checking Explanationscited by 132
  19. 2020Break It Down: A Question Understanding Benchmarkcited by 131
  20. 2023WiCE: Real-World Entailment for Claims in Wikipediacited by 120
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  22. 2020Unsupervised Question Decomposition for Question Answeringcited by 118
  23. 2022Training Language Models with Memory Augmentationcited by 113
  24. 2021Decontextualization: Making Sentences Stand-Alonecited by 102
  25. 2018DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learningcited by 100
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  27. 2020Relevance-guided Supervision for OpenQA with ColBERTcited by 71
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  35. 2022Varifocal Question Generation for Fact-checkingcited by 27
  36. 2021The Case for Claim Difficulty Assessment in Automatic Fact Checkingcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 11; 2024: 39; 2025: 44; 2026: 16.

110 papers.

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  1. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,601
  2. 2023RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentationcited by 256
  3. 2024Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Mapscited by 142
  4. 2024VERISCORE: Evaluating the factuality of verifiable claims in long-form text generationcited by 117
  5. 2024Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Eracited by 98
  6. 2024ContextCite: Attributing Model Generation to Contextcited by 98
  7. 2023ExpertQA: Expert-Curated Questions and Attributed Answerscited by 97
  8. 2023Cognitive Mirage: A Review of Hallucinations in Large Language Modelscited by 84
  9. 2023A Survey of Large Language Models Attributioncited by 71
  10. 2024Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systemscited by 66
  11. 2024Do LLMs Know about Hallucination? An Empirical Investigation of LLM's Hidden Statescited by 52
  12. 2023Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrongcited by 51
38 more
  1. 2024CiteME: Can Language Models Accurately Cite Scientific Claims?cited by 48
  2. 2024Molecular Facts: Desiderata for Decontextualization in LLM Fact Verificationcited by 44
  3. 2024Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Modelscited by 44
  4. 2024A Closer Look at Claim Decompositioncited by 41
  5. 2024Decomposition Dilemmas: Does Claim Decomposition Boost or Burden Fact-Checking Performance?cited by 36
  6. 2024Retrieval Augmented Fact Verification by Synthesizing Contrastive Argumentscited by 25
  7. 2024Claim Verification in the Age of Large Language Models: A Surveycited by 24
  8. 2025Hallucination Detection in Large Language Models with Metamorphic Relationscited by 24
  9. 2024AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attributioncited by 23
  10. 2024DnDScore: Decontextualization and Decomposition for Factuality Verification in Long-Form Text Generationcited by 22
  11. 2024A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagationcited by 21
  12. 2024Atomic Fact Decomposition Helps Attributed Question Answeringcited by 21
  13. 2023Sub-Sentence Encoder: Contrastive Learning of Propositional Semantic Representationscited by 20
  14. 2024ECon: On the Detection and Resolution of Evidence Conflictscited by 18
  15. 2024Ev2R: Evaluating Evidence Retrieval in Automated Fact-Checkingcited by 18
  16. 2025AVerImaTeC: A Dataset for Automatic Verification of Image-Text Claims with Evidence from the Webcited by 18
  17. 2025RvLLM: LLM Runtime Verification with Domain Knowledgecited by 17
  18. 2025Resolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMscited by 16
  19. 2024Reinforcement Retrieval Leveraging Fine-grained Feedback for Fact Checking News Claims with Black-Box LLMcited by 15
  20. 2024Hallucination Detection in LLMs: Fast and Memory-Efficient Fine-Tuned Modelscited by 15
  21. 2025TokenShapley: Token Level Context Attribution with Shapley Valuecited by 15
  22. 2025HalluEntity: Benchmarking and Understanding Entity-Level Hallucination Detectioncited by 13
  23. 2025Zero-shot and Few-shot Learning with Instruction-following LLMs for Claim Matching in Automated Fact-checkingcited by 12
  24. 2023Using Natural Language Explanations to Rescale Human Judgmentscited by 11
  25. 2024Retrieval-Enhanced Machine Learning: Synthesis and Opportunitiescited by 11
  26. 2024Open-World Evaluation for Retrieving Diverse Perspectivescited by 11
  27. 2025NLI under the Microscope: What Atomic Hypothesis Decomposition Revealscited by 11
  28. 2025EvalAgent: Discovering Implicit Evaluation Criteria from the Webcited by 11
  29. 2025Optimizing Decomposition for Optimal Claim Verificationcited by 10
  30. 2023Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AIcited by 9
  31. 2024Automatic Generation of Model and Data Cards: A Step Towards Responsible AIcited by 9
  32. 2024SEER: Self-Aligned Evidence Extraction for Retrieval-Augmented Generationcited by 9
  33. 2025Shadows in the Attention: Contextual Perturbation and Representation Drift in the Dynamics of Hallucination in LLMscited by 9
  34. 2023AMERICANO: Argument Generation with Discourse-driven Decomposition and Agent Interactioncited by 8
  35. 2024A Survey on Responsible Generative AI: What to Generate and What Notcited by 8
  36. 2025Verify with Caution: The Pitfalls of Relying on Imperfect Factuality Metricscited by 8
  37. 2025Truth over Tricks: Measuring and Mitigating Shortcut Learning in Misinformation Detectioncited by 8
  38. 2024WebCiteS: Attributed Query-Focused Summarization on Chinese Web Search Results with Citationscited by 7

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