
AI-hallucinated citations are creeping into papers that shape clinical guidelines, researchers warn
Quick Answer
An audit of 2.5 million biomedical papers reveals a twelvefold increase in AI-generated fake citations since 2023, likely linked to language model usage.
Quick Take
An audit of 2.5 million biomedical papers reveals a twelvefold increase in AI-generated fake citations since 2023, likely linked to language model usage. 98% of affected papers have not received publisher responses, raising concerns about the integrity of clinical guidelines.
Key Points
- The rate of fabricated references in biomedical papers has surged over 1200% since 2023.
- AI-generated citations often match paper topics and are formatted correctly, making them hard to detect.
- Columbia University conducted the audit alongside other institutions, examining 2.5 million papers.
- 98% of the papers with fake citations have not received any response from publishers.
- Concerns are rising about the impact of these citations on clinical guidelines.
Article Excerpt
From source RSS / original summaryAn audit of 2. 5 million biomedical papers by Columbia University and other institutions shows that the rate of fabricated references has increased more than twelvefold since 2023. The researchers suspect a link to the widespread use of language models - the fake references match their paper's topic, follow correct formatting, and are nearly impossible to spot. 98 percent of the affected papers have received no response from their publishers.
The article AI-hallucinated citations are creeping into papers that shape clinical guidelines, researchers warn appeared first on The Decoder.
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from The Decoder
See more →
An AI model programmed nonstop for 19 days on a single MirrorCode task that cost $2,600 to run
Epoch AI's MirrorCode benchmark reveals Claude Opus 4.7 as the leader with a 56% solve rate, reconstructing a 16,000-line toolkit in 14 hours. Despite this, all models tested struggle with the most complex tasks, highlighting limitations in current AI capabilities. The single task consumed $2,600 over 19 days, raising questions about cost-effectiveness in AI development.

