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AI Models Could Break Double-Blind Peer Review

Researchers found that large language models (LLMs) can often identify anonymous academic papers. This threatens the integrity of double-blind peer review, which relies on anonymity to prevent bias. The study shows that LLMs can match titles and abstracts to authors, even without full access to the papers.

via ArXiv cs.CL#AI#Research#Academic