ChatGPT: Excellent Paper Accept It. Editor: Imposter Found Review Rejected (arxiv.org)

A recent paper titled "ChatGPT: Excellent Paper! Accept It. Editor: Imposter Found! Review Rejected" highlights the dual-edged influence of Large Language Models (LLMs) in academic publishing, particularly in cryptography and security. As LLMs like ChatGPT gain traction in writing and reviewing scientific papers, there are mounting concerns regarding their effects on research integrity. The study reveals that LLM-generated content can lead to the submission of flawed studies, which pose significant risks to trust and safety, especially in critical fields like medicine. To address these challenges, the research proposes an innovative "inject-and-detect" strategy for editorial review processes, embedding invisible prompts within papers that can signal when a review is generated by an LLM. This method enables editors to identify and combat bias by effectively turning vulnerabilities into verification tools. By improving awareness among editors and enhancing the peer-review process, the proposed approach aims to mitigate the risks of LLM influence, restoring trust in scientific evaluations and promoting rigorous standards in research.