mlsanityData to 7 Oct 2026

Evidence-backed Fact Checking using RAG and Few-Shot In-Context Learning with LLMs

arXiv 2408.12060 ↗First posted 22 Aug 2024cs.CL cs.AIcited by 23

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Abstract (arXiv)

Given the widespread dissemination of misinformation on social media, implementing fact-checking mechanisms for online claims is essential. Manually verifying every claim is very challenging, underscoring the need for an automated fact-checking system. This paper presents our system designed to address this issue. We utilize the Averitec dataset (Schlichtkrull et al., 2023) to assess the performance of our fact-checking system. In addition to veracity prediction, our system provides supporting evidence, which is extracted from the dataset. We develop a Retrieve and Generate (RAG) pipeline to extract relevant evidence sentences from a knowledge base, which are then inputted along with the claim into a large language model (LLM) for classification. We also evaluate the few-shot In-Context Learning (ICL) capabilities of multiple LLMs. Our system achieves an 'Averitec' score of 0.33, which is a 22% absolute improvement over the baseline. Our Code is publicly available on https://github.com/ronit-singhal/evidence-backed-fact-checking-using-rag-and-few-shot-in-context-learning-with-llms.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Builds on 23 of its 45 references that are in the map. First posted on arXiv 22 Aug 2024.

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23 of 45 references.

References · 23

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2024The Llama 3 Herd of Modelscited by 14,192
  3. 2024Qwen2 Technical Reportcited by 2,076
  4. 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,968
  5. 2024Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonecited by 1,883
  6. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,362
  7. 2022Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learningcited by 886
  8. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  9. 2021A Survey on Automated Fact-Checkingcited by 376
  10. 2021Get Your Vitamin C! Robust Fact Verification with Contrastive Evidencecited by 222
  11. 2023AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Webcited by 144
  12. 2023Towards LLM-based Fact Verification on News Claims with a Hierarchical Step-by-Step Prompting Methodcited by 97
11 more
  1. 2018Automated Fact Checking: Task formulations, methods and future directionscited by 96
  2. 2020Explainable Automated Fact-Checking: A Surveycited by 83
  3. 2020Fighting an Infodemic: COVID-19 Fake News Datasetcited by 82
  4. 2021ProoFVer: Natural Logic Theorem Proving for Fact Verificationcited by 52
  5. 2024Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debatecited by 48
  6. 2018Integrating Stance Detection and Fact Checking in a Unified Corpuscited by 41
  7. 2023Factify 2: A Multimodal Fake News and Satire News Datasetcited by 23
  8. 2024CrAM: Credibility-Aware Attention Modification in LLMs for Combating Misinformation in RAGcited by 22
  9. 2020g2tmn at Constraint@AAAI2021: Exploiting CT-BERT and Ensembling Learning for COVID-19 Fake News Detectioncited by 14
  10. 2024Enhancing Low-Resource LLMs Classification with PEFT and Synthetic Datacited by 7
  11. 2021COVID-19 Tests Gone Rogue: Privacy, Efficacy, Mismanagement and Misunderstandingscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 13; 2026: 9.

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  1. 2024The Automated Verification of Textual Claims (AVeriTeC) Shared Taskcited by 29
  2. 2025Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Modelscited by 13
  3. 2025A Survey of Scaling in Large Language Model Reasoningcited by 10
  4. 2025The Next Phase of Scientific Fact-Checking: Advanced Evidence Retrieval from Complex Structured Academic Paperscited by 6
  5. 2025Towards Geo-Culturally Grounded LLM Generationscited by 5
  6. 2025HintsOfTruth: A Multimodal Checkworthiness Detection Dataset with Real and Synthetic Claimscited by 4
  7. 2025Uncovering the Bigger Picture: Comprehensive Event Understanding Via Diverse News Retrievalcited by 4
  8. 2025Task-Oriented Automatic Fact-Checking with Frame-Semanticscited by 3
  9. 2025EMULATE: A Multi-Agent Framework for Determining the Veracity of Atomic Claims by Emulating Human Actionscited by 3
  10. 2025A Comprehensive Dataset for Human vs. AI Generated Text Detectioncited by 3
  11. 2025SocialDF: Benchmark Dataset and Detection Model for Mitigating Harmful Deepfake Content on Social Media Platformscited by 2
  12. 2025Fact in Fragments: Deconstructing Complex Claims via LLM-based Atomic Fact Extraction and Verificationcited by 2
11 more
  1. 2026RAG over Thinking Traces Can Improve Reasoning Taskscited by 2
  2. 2026Shared Nature, Unique Nurture: PRISM for Pluralistic Reasoning via In-context Structure Modelingcited by 1
  3. 2025Automatic Fact-checking in English and Telugucited by 0
  4. 2025Use of Retrieval-Augmented Large Language Model Agent for Long-Form COVID-19 Fact-Checkingcited by 0
  5. 2026Frame-Guided Synthetic Claim Generation for Automatic Fact-Checking Using High-Volume Tabular Datacited by 0
  6. 2026Agentic Adversarial Rewriting Exposes Architectural Vulnerabilities in Black-Box NLP Pipelinescited by 0
  7. 2026The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modescited by 0
  8. 2026Generating Biomedical Fact-Checking Reports with RL-Enhanced Agentic Searchcited by 0
  9. 2026Detecting and Explaining Fake News Short Videos with Multimodal Content and Real-World Evidencecited by 0
  10. 2026Medical Knowledge Simplification for Patients in the Era of LLMs: A Case Study on Diabetescited by 0
  11. 2026EvidenT: Building Trustworthy Enterprise Assistants through Evidence Groundedness and Traceabilitycited by 0

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  1. 2024AIC CTU system at AVeriTeC: Re-framing automated fact-checking as a simple RAG task
  2. 2026Evaluating and Improving Evidence-Grounded Fact-Checking in LLMs via Multi-Round Evidence Ablation
  3. 2025Resolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMs
  4. 2025Fact-checking AI-generated news reports: Can LLMs catch their own lies?
  5. 2025Towards Automated Fact-Checking of Real-World Claims: Exploring Task Formulation and Assessment with LLMs
  6. 2026Diagnosing LLM Arbitration Behavior over Pre-evidence Epistemic States in RAG-based Fact-Checking
  7. 2026InFi-Check: Interpretable and Fine-Grained Fact-Checking of LLMs
  8. 2025Can LLMs extract human-like fine-grained evidence for evidence-based fact-checking?