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Illustration: Adam Wójcicki

Earlier this year, computer scientist Guillaume Cabanac received a notification from Google Scholar that one of his publications had been cited in a paper published in the International Dental Journal1. That was unexpected, because his research on spotting fabricated papers doesn’t typically intersect with dentistry. “I was very surprised to see that I couldn’t recognize my own reference,” says Cabanac, who is based at the University of Toulouse in France.

The title in the citation resembled that of a preprint2 he had posted in 2021 and never published formally, but the journal was listed as Nature and the DOI — the unique identifier assigned by publishers and preprint repositories — did not lead to the original preprint. “I got very concerned,” adds Cabanac, who immediately suspected that the citation had been hallucinated by artificial intelligence.

This is just one example of a rapidly growing problem. Surveys and related studies have shown that researchers are increasingly using large language models (LLMs) to help to conduct literature searches, write manuscripts and format bibliographies. And sometimes, these models generate non-existent academic references.

Is AI leading to a reproducibility crisis in science?

Hallucinated citations are polluting the scientific literature. What can be done?