mlsanityData to 7 Oct 2026

LLM-Generated Fake News Induces Truth Decay in News Ecosystem: A Case Study on Neural News Recommendation

arXiv 2504.20013 ↗First posted 28 Apr 2025cs.CL cs.CY cs.IRcited by 19

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Abstract (arXiv)

Online fake news moderation now faces a new challenge brought by the malicious use of large language models (LLMs) in fake news production. Though existing works have shown LLM-generated fake news is hard to detect from an individual aspect, it remains underexplored how its large-scale release will impact the news ecosystem. In this study, we develop a simulation pipeline and a dataset with ~56k generated news of diverse types to investigate the effects of LLM-generated fake news within neural news recommendation systems. Our findings expose a truth decay phenomenon, where real news is gradually losing its advantageous position in news ranking against fake news as LLM-generated news is involved in news recommendation. We further provide an explanation about why truth decay occurs from a familiarity perspective and show the positive correlation between perplexity and news ranking. Finally, we discuss the threats of LLM-generated fake news and provide possible countermeasures. We urge stakeholders to address this emerging challenge to preserve the integrity of news ecosystems.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). Builds on 31 of its 64 references that are in the map. First posted on arXiv 28 Apr 2025.

Builds on

31 of 64 references.

References · 31

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2020Language Models are Few-Shot Learnerscited by 32,199
  4. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
  5. 2019Defending Against Neural Fake Newscited by 553
  6. 2018FakeNewsNet: A Data Repository with News Content, Social Context and Spatialtemporal Information for Studying Fake News on Social Mediacited by 281
  7. 2023Can LLM-Generated Misinformation Be Detected?cited by 173
  8. 2024Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviewscited by 160
  9. 2023Combating Misinformation in the Age of LLMs: Opportunities and Challengescited by 94
  10. 2023AI model GPT-3 (dis)informs us better than humanscited by 75
  11. 2023Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detectioncited by 69
  12. 2023Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attackscited by 69
19 more
  1. 2021Empowering News Recommendation with Pre-trained Language Modelscited by 63
  2. 2020ReCOVery: A Multimodal Repository for COVID-19 News Credibility Researchcited by 44
  3. 2022Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data Generationcited by 41
  4. 2023Disinformation Detection: An Evolving Challenge in the Age of LLMscited by 41
  5. 2023Neural Retrievers are Biased Towards LLM-Generated Contentcited by 37
  6. 2022Zoom Out and Observe: News Environment Perception for Fake News Detectioncited by 34
  7. 2019Combating Fake News: A Survey on Identification and Mitigation Techniquescited by 33
  8. 2024Exploring the Deceptive Power of LLM-Generated Fake News: A Study of Real-World Detection Challengescited by 28
  9. 2020Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repositorycited by 25
  10. 2024Ten Words Only Still Help: Improving Black-Box AI-Generated Text Detection via Proxy-Guided Efficient Re-Samplingcited by 20
  11. 2024Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integrationcited by 17
  12. 2023Combating Online Misinformation Videos: Characterization, Detection, and Future Directionscited by 14
  13. 2024Generative News Recommendationcited by 10
  14. 2023RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Modelscited by 6
  15. 2024Spiral of Silence: How is Large Language Model Killing Information Retrieval? -- A Case Study on Open Domain Question Answeringcited by 5
  16. 2025Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documentscited by 5
  17. 2021Analysing the Effect of Recommendation Algorithms on the Amplification of Misinformationcited by 4
  18. 2023Exploring Fine-tuning ChatGPT for News Recommendationcited by 3
  19. 2023PUNR: Pre-training with User Behavior Modeling for News Recommendationcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 8; 2026: 11.

19 papers.

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  1. 2026JailNewsBench: Multi-Lingual and Regional Benchmark for Fake News Generation under Jailbreak Attackscited by 6
  2. 2025Long-Form Information Alignment Evaluation Beyond Atomic Factscited by 4
  3. 2025Prompt-Induced Linguistic Fingerprints for LLM-Generated Fake News Detectioncited by 3
  4. 2025Reasoning About the Unsaid: Misinformation Detection with Omission-Aware Graph Inferencecited by 3
  5. 2026Beyond the Final Actor: Modeling the Dual Roles of Creator and Editor for Fine-Grained LLM-Generated Text Detectioncited by 3
  6. 2026LiveFact: A Dynamic, Time-Aware Benchmark for LLM-Driven Fake News Detectioncited by 2
  7. 2025Forewarned is Forearmed: Pre-Synthesizing Jailbreak-like Instructions to Enhance LLM Safety Guardrail to Potential Attackscited by 1
  8. 2025A Survey of the State-of-the-Art in Conversational Question Answering Systemscited by 1
  9. 2025CogniDir: Combating Cognitive Malicious Comments via Adaptive Distributional Learning for Robust Fake News Detectioncited by 1
  10. 2025SARC: Sentiment-Augmented Deep Role Clustering for Fake News Detectioncited by 0
  11. 2025Can We Stop Malicious AI? KILLBENCH: A Benchmark for External AI Kill Switch Feasibilitycited by 0
  12. 2026CoT is Not the Chain of Truth: An Empirical Internal Analysis of Reasoning LLMs for Fake News Generationcited by 0
7 more
  1. 2026Enhancing Debunking Effectiveness through LLM-based Personality Adaptationcited by 0
  2. 2026Many Ways to Be Fake: Benchmarking Fake News Detection Under Strategy-Driven AI Generationcited by 0
  3. 2026LLMs Should Incorporate Explicit Mechanisms for Human Empathycited by 0
  4. 2026Luminol-AIDetect: Fast Zero-shot Machine-Generated Text Detection based on Perplexity under Text Shufflingcited by 0
  5. 2026Logical Consistency as a Bridge: Improving LLM Hallucination Detection via Label Constraint Modeling between Responses and Self-Judgmentscited by 0
  6. 2026Large Language Models in Misinformation Ecosystems: Misuse, Defense, and Vulnerabilitycited by 0
  7. 2026Enhancing LLMs with Context-Specific Knowledge for Mitigating Misinformation in SMEs: A RAG-based Modeling and Analysiscited by 0