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

arXiv: https://arxiv.org/abs/2504.20013 · HTML: https://mlsanity.com/paper/2504.20013/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- Builds on 31 of its 64 references that are in the map.
- First posted on arXiv 28 Apr 2025.

## Builds on (most cited first, 30 of 31)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback](https://mlsanity.com/paper/2204.05862/) (2022)
- [Defending Against Neural Fake News](https://mlsanity.com/paper/1905.12616/) (2019)
- [FakeNewsNet: A Data Repository with News Content, Social Context and Spatialtemporal Information for Studying Fake News on Social Media](https://mlsanity.com/paper/1809.01286/) (2018)
- [Can LLM-Generated Misinformation Be Detected?](https://mlsanity.com/paper/2309.13788/) (2023)
- [Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews](https://mlsanity.com/paper/2403.07183/) (2024)
- [Combating Misinformation in the Age of LLMs: Opportunities and Challenges](https://mlsanity.com/paper/2311.05656/) (2023)
- [AI model GPT-3 (dis)informs us better than humans](https://mlsanity.com/paper/2301.11924/) (2023)
- [Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detection](https://mlsanity.com/paper/2309.12247/) (2023)
- [Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks](https://mlsanity.com/paper/2310.10830/) (2023)
- [Empowering News Recommendation with Pre-trained Language Models](https://mlsanity.com/paper/2104.07413/) (2021)
- [ReCOVery: A Multimodal Repository for COVID-19 News Credibility Research](https://mlsanity.com/paper/2006.05557/) (2020)
- [Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data Generation](https://mlsanity.com/paper/2203.05386/) (2022)
- [Disinformation Detection: An Evolving Challenge in the Age of LLMs](https://mlsanity.com/paper/2309.15847/) (2023)
- [Neural Retrievers are Biased Towards LLM-Generated Content](https://mlsanity.com/paper/2310.20501/) (2023)
- [Zoom Out and Observe: News Environment Perception for Fake News Detection](https://mlsanity.com/paper/2203.10885/) (2022)
- [Combating Fake News: A Survey on Identification and Mitigation Techniques](https://mlsanity.com/paper/1901.06437/) (2019)
- [Exploring the Deceptive Power of LLM-Generated Fake News: A Study of Real-World Detection Challenges](https://mlsanity.com/paper/2403.18249/) (2024)
- [Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository](https://mlsanity.com/paper/2002.00837/) (2020)
- [Ten Words Only Still Help: Improving Black-Box AI-Generated Text Detection via Proxy-Guided Efficient Re-Sampling](https://mlsanity.com/paper/2402.09199/) (2024)
- [Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration](https://mlsanity.com/paper/2405.16546/) (2024)
- [Combating Online Misinformation Videos: Characterization, Detection, and Future Directions](https://mlsanity.com/paper/2302.03242/) (2023)
- [Generative News Recommendation](https://mlsanity.com/paper/2403.03424/) (2024)
- [RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Models](https://mlsanity.com/paper/2312.10463/) (2023)
- [Spiral of Silence: How is Large Language Model Killing Information Retrieval? -- A Case Study on Open Domain Question Answering](https://mlsanity.com/paper/2404.10496/) (2024)
- [Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents](https://mlsanity.com/paper/2503.08684/) (2025)
- [Analysing the Effect of Recommendation Algorithms on the Amplification of Misinformation](https://mlsanity.com/paper/2103.14748/) (2021)
- [Exploring Fine-tuning ChatGPT for News Recommendation](https://mlsanity.com/paper/2311.05850/) (2023)

## Built on by (most cited first, 19 of 19)

- [JailNewsBench: Multi-Lingual and Regional Benchmark for Fake News Generation under Jailbreak Attacks](https://mlsanity.com/paper/2603.01291/) (2026)
- [Long-Form Information Alignment Evaluation Beyond Atomic Facts](https://mlsanity.com/paper/2505.15792/) (2025)
- [Prompt-Induced Linguistic Fingerprints for LLM-Generated Fake News Detection](https://mlsanity.com/paper/2508.12632/) (2025)
- [Reasoning About the Unsaid: Misinformation Detection with Omission-Aware Graph Inference](https://mlsanity.com/paper/2512.01728/) (2025)
- [Beyond the Final Actor: Modeling the Dual Roles of Creator and Editor for Fine-Grained LLM-Generated Text Detection](https://mlsanity.com/paper/2604.04932/) (2026)
- [LiveFact: A Dynamic, Time-Aware Benchmark for LLM-Driven Fake News Detection](https://mlsanity.com/paper/2604.04815/) (2026)
- [Forewarned is Forearmed: Pre-Synthesizing Jailbreak-like Instructions to Enhance LLM Safety Guardrail to Potential Attacks](https://mlsanity.com/paper/2508.20038/) (2025)
- [A Survey of the State-of-the-Art in Conversational Question Answering Systems](https://mlsanity.com/paper/2509.05716/) (2025)
- [CogniDir: Combating Cognitive Malicious Comments via Adaptive Distributional Learning for Robust Fake News Detection](https://mlsanity.com/paper/2510.09712/) (2025)
- [Luminol-AIDetect: Fast Zero-shot Machine-Generated Text Detection based on Perplexity under Text Shuffling](https://mlsanity.com/paper/2604.25860/) (2026)
- [SARC: Sentiment-Augmented Deep Role Clustering for Fake News Detection](https://mlsanity.com/paper/2511.04692/) (2025)
- [Can We Stop Malicious AI? KILLBENCH: A Benchmark for External AI Kill Switch Feasibility](https://mlsanity.com/paper/2511.13725/) (2025)
- [CoT is Not the Chain of Truth: An Empirical Internal Analysis of Reasoning LLMs for Fake News Generation](https://mlsanity.com/paper/2602.04856/) (2026)
- [Enhancing Debunking Effectiveness through LLM-based Personality Adaptation](https://mlsanity.com/paper/2603.09533/) (2026)
- [Many Ways to Be Fake: Benchmarking Fake News Detection Under Strategy-Driven AI Generation](https://mlsanity.com/paper/2604.09514/) (2026)
- [LLMs Should Incorporate Explicit Mechanisms for Human Empathy](https://mlsanity.com/paper/2604.10557/) (2026)
- [Logical Consistency as a Bridge: Improving LLM Hallucination Detection via Label Constraint Modeling between Responses and Self-Judgments](https://mlsanity.com/paper/2605.03971/) (2026)
- [Large Language Models in Misinformation Ecosystems: Misuse, Defense, and Vulnerability](https://mlsanity.com/paper/2607.10402/) (2026)
- [Enhancing LLMs with Context-Specific Knowledge for Mitigating Misinformation in SMEs: A RAG-based Modeling and Analysis](https://mlsanity.com/paper/2608.00006/) (2026)

## 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.