mlsanityData to 7 Oct 2026

Industrialized Deception: The Collateral Effects of LLM-Generated Misinformation on Digital Ecosystems

arXiv 2601.21963 ↗First posted 29 Jan 2026cs.CY cs.AI cs.CLcited by 7

Not on the map. Why?

Abstract (arXiv)

Generative AI and misinformation research has evolved since our 2024 survey. This paper presents an updated perspective, transitioning from literature review to practical countermeasures. We report on changes in the threat landscape, including improved AI-generated content through Large Language Models (LLMs) and multimodal systems. Central to this work are our practical contributions: JudgeGPT, a platform for evaluating human perception of AI-generated news, and RogueGPT, a controlled stimulus generation engine for research. Together, these tools form an experimental pipeline for studying how humans perceive and detect AI-generated misinformation. Our findings show that detection capabilities have improved, but the competition between generation and detection continues. We discuss mitigation strategies including LLM-based detection, inoculation approaches, and the dual-use nature of generative AI. This work contributes to research addressing the adverse impacts of AI on information quality.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 18 of its 63 references that are in the map. First posted on arXiv 29 Jan 2026.

Builds on

18 of 63 references.

References · 18

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2022Generative Adversarial Networkscited by 5,603
  3. 2024The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bitscited by 289
  4. 2023A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPTcited by 221
  5. 2024Design Principles for Generative AI Applicationscited by 57
  6. 2023GenAI Against Humanity: Nefarious Applications of Generative Artificial Intelligence and Large Language Modelscited by 40
  7. 2020Combating Disinformation in a Social Media Agecited by 17
  8. 2024From Deception to Detection: The Dual Roles of Large Language Models in Fake Newscited by 11
  9. 2024Understanding Knowledge Drift in LLMs through Misinformationcited by 9
  10. 2026Robust Fake News Detection using Large Language Models under Adversarial Sentiment Attackscited by 7
  11. 2026The Paradigm Shift: A Comprehensive Survey on Large Vision Language Models for Multimodal Fake News Detectioncited by 6
  12. 2026The Generative AI Paradox: GenAI and the Erosion of Trust, the Corrosion of Information Verification, and the Demise of Truthcited by 4
6 more
  1. 2025Understanding Reader Perception Shifts upon Disclosure of AI Authorshipcited by 3
  2. 2025Simulating Misinformation Propagation in Social Networks using Large Language Modelscited by 3
  3. 2025Toward Generalized Detection of Synthetic Media: Limitations, Challenges, and the Path to Multimodal Solutionscited by 2
  4. 2025Agentic Multi-Persona Framework for Evidence-Aware Fake News Detectioncited by 1
  5. 2026MultiCaption: Detecting disinformation using multilingual visual claimscited by 1
  6. 2026An Agentic Operationalization of DISARM for FIMI Investigation on Social Mediacited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 7.

7 papers.

  1. 2026Eroding the Truth-Default: A Causal Analysis of Human Susceptibility to Foundation Model Hallucinations and Disinformation in the Wildcited by 3
  2. 2026Origin Lens: A Privacy-First Mobile Framework for Cryptographic Image Provenance and AI Detectioncited by 2
  3. 2026The Verification Crisis: Expert Perceptions of GenAI Disinformation and the Case for Reproducible Provenancecited by 1
  4. 2026Can Humans Tell? A Dual-Axis Study of Human Perception of LLM-Generated Newscited by 1
  5. 2026ExTax: Explainable Disinformation Detection via Persuasion, Emotion, and Narrative Role Taxonomiescited by 0
  6. 2026Interrupting the Chain: Human Perception of AI-Generated Disinformation Through a Kill Chain Lenscited by 0
  7. 2026The Tokens Remember: When Tokenization Bypasses Knowledge Editing and Unlearningcited by 0