https://www.nature.com/articles/d41586-025-03506-6
"What can researchers do if they suspect that their manuscripts have been peer
reviewed using artificial intelligence (AI)? Dozens of academics have raised
concerns on social media about manuscripts and peer reviews submitted to the
organizers of next year’s International Conference on Learning Representations
(ICLR), an annual gathering of specialists in machine learning. Among other
things, they flagged hallucinated citations and suspiciously long and vague
feedback on their work.
Graham Neubig, an AI researcher at Carnegie Mellon University in Pittsburgh,
Pennsylvania, was one of those who received peer reviews that seemed to have
been produced using large language models (LLMs). The reports, he says, were
“very verbose with lots of bullet points” and requested analyses that were not
“the standard statistical analyses that reviewers ask for in typical AI or
machine-learning papers.”
But Neubig needed help proving that the reports were AI-generated. So, he
posted on X (formerly Twitter) and offered a reward for anyone who could scan
all the conference submissions and their peer reviews for AI-generated text.
The next day, he got a response from Max Spero, chief executive of Pangram Labs
in New York City, which develops tools to detect AI-generated text. Pangram
screened all 19,490 studies and 75,800 peer reviews submitted for ICLR 2026,
which will take place in Rio de Janeiro, Brazil, in April. Neubig and more than
11,000 other AI researchers will be attending.
Pangram’s analysis revealed that around 21% of the ICLR peer reviews were fully
AI-generated, and more than half contained signs of AI use. The findings were
posted online by Pangram Labs. “People were suspicious, but they didn’t have
any concrete proof,” says Spero. “Over the course of 12 hours, we wrote some
code to parse out all of the text content from these paper submissions,” he
adds.
The conference organizers say they will now use automated tools to assess
whether submissions and peer reviews breached policies on using AI in
submissions and peer reviews. This is the first time that the conference has
faced this issue at scale, says Bharath Hariharan, a computer scientist at
Cornell University in Ithaca, New York, and senior programme chair for ICLR
2026. “After we go through all this process … that will give us a better notion
of trust.”"
Via Christoph S.
Cheers,
*** Xanni ***
--
mailto:xanni@xanadu.net Andrew Pam
http://xanadu.com.au/ Chief Scientist, Xanadu
https://glasswings.com.au/ Partner, Glass Wings
https://sericyb.com.au/ Manager, Serious Cybernetics
