mlsanityData to 7 Oct 2026

The Rise of AI-Generated Content in Wikipedia

arXiv 2410.08044 ↗First posted 10 Oct 2024cs.CLcited by 22

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Abstract (arXiv)

The rise of AI-generated content in popular information sources raises significant concerns about accountability, accuracy, and bias amplification. Beyond directly impacting consumers, the widespread presence of this content poses questions for the long-term viability of training language models on vast internet sweeps. We use GPTZero, a proprietary AI detector, and Binoculars, an open-source alternative, to establish lower bounds on the presence of AI-generated content in recently created Wikipedia pages. Both detectors reveal a marked increase in AI-generated content in recent pages compared to those from before the release of GPT-3.5. With thresholds calibrated to achieve a 1% false positive rate on pre-GPT-3.5 articles, detectors flag over 5% of newly created English Wikipedia articles as AI-generated, with lower percentages for German, French, and Italian articles. Flagged Wikipedia articles are typically of lower quality and are often self-promotional or partial towards a specific viewpoint on controversial topics.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 13 of its 36 references that are in the map. First posted on arXiv 10 Oct 2024.

Builds on

13 of 36 references.

References · 13

  1. 2023How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detectioncited by 472
  2. 2023Can AI-Generated Text be Reliably Detected?cited by 372
  3. 2023How Good Are GPT Models at Machine Translation? A Comprehensive Evaluationcited by 344
  4. 2023Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvaturecited by 278
  5. 2024Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Textcited by 255
  6. 2023GPT detectors are biased against non-native English writerscited by 175
  7. 2023Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigationscited by 157
  8. 2023The Science of Detecting LLM-Generated Textscited by 126
  9. 2023M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detectioncited by 118
  10. 2024Mapping the Increasing Use of LLMs in Scientific Paperscited by 112
  11. 2024The AI Review Lottery: Widespread AI-Assisted Peer Reviews Boost Paper Scores and Acceptance Ratescited by 66
  12. 2019Generating Sentiment-Preserving Fake Online Reviews Using Neural Language Models and Their Human- and Machine-based Detectioncited by 50
1 more
  1. 2024MAiDE-up: Multilingual Deception Detection of GPT-generated Hotel Reviewscited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 15; 2026: 7.

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  1. 2025The Widespread Adoption of Large Language Model-Assisted Writing Across Societycited by 50
  2. 2025Detecting Stylistic Fingerprints of Large Language Modelscited by 11
  3. 2025AI use in American newspapers is widespread, uneven, and rarely disclosedcited by 9
  4. 2025Large Language Models Penetration in Scholarly Writing and Peer Reviewcited by 6
  5. 2025WETBench: A Benchmark for Detecting Task-Specific Machine-Generated Text on Wikipediacited by 6
  6. 2025When Incentives Backfire, Data Stops Being Humancited by 4
  7. 2025Wikipedia in the Era of LLMs: Evolution and Riskscited by 4
  8. 2026Deep-Research Agents Can Be Poisoned via User-Generated Contentcited by 4
  9. 2025DACTYL: Diverse Adversarial Corpus of Texts Yielded from Large Language Modelscited by 3
  10. 2025On the Detectability of LLM-Generated Text: What Exactly Is LLM-Generated Text?cited by 3
  11. 2025Did ChatGPT or Copilot use alter the style of internet news headlines? A time series regression analysiscited by 2
  12. 2026TSM-Bench: Detecting LLM-Generated Text in Real-World Wikipedia Editing Practicescited by 2
10 more
  1. 2025Man Made Language Models? Evaluating LLMs' Perpetuation of Masculine Generics Biascited by 1
  2. 2025Beyond speculation: Measuring the growing presence of LLM-generated texts in multilingual disinformationcited by 1
  3. 2025Wikipedia is Not a Dictionary, Delete! Text Classification as a Proxy for Analysing Wiki Deletion Discussionscited by 0
  4. 2025Stylometry recognizes human and LLM-generated texts in short samplescited by 0
  5. 2025Towards Inclusive Toxic Content Moderation: Addressing Vulnerabilities to Adversarial Attacks in Toxicity Classifiers Tackling LLM-generated Contentcited by 0
  6. 2026From Collapse to Improvement: Statistical Perspectives on the Evolutionary Dynamics of Iterative Training on Contaminated Sourcescited by 0
  7. 2026Can Generative Artificial Intelligence Survive Data Contamination? Theoretical Guarantees under Contaminated Recursive Trainingcited by 0
  8. 2026Beyond Detection: Rethinking Education in the Age of AI-writingcited by 0
  9. 2026SlopShape: Identifying AI-Generated Commercial Web Contentcited by 0
  10. 2026Narrowing the Horizon: Quantifying Topic Saliency Shifts in Generative Monoculturecited by 0