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New arXiv policy: 1-year ban for hallucinated references (twitter.com)

659 points by gjuggler · 60 days ago · 230 comments on HN

Article summary

ArXiv has introduced a new policy where authors who include hallucinated references in their submissions will face a 1-year ban, followed by a requirement for subsequent submissions to be accepted at a reputable peer-reviewed venue. The policy aims to address the issue of fake or inaccurate references in academic papers. The discussion around this policy reveals concerns about academic integrity and the role of AI in research. The policy's effectiveness and fairness are being debated.

Main themes

  • Academic integrity
  • AI in research
  • Reference verification
  • Research ethics
  • Publication policies

What commenters say

  • Including hallucinated references in academic papers is a serious offense that undermines the integrity of research and deserves strict penalties.
  • The new policy is a necessary measure to prevent the spread of misinformation and ensure the credibility of academic publications.
  • A 1-year ban for a single hallucinated reference may be too harsh, as it does not account for the substance or quality of the research, and may unfairly punish honest researchers who make minor mistakes.
  • Relying on AI to generate citations without verifying their accuracy is a form of negligence and can lead to fraudulent behavior.
  • The policy does not distinguish between intentional fraud and honest mistakes, and may unfairly penalize researchers who are unaware of the inaccuracies in their citations.
  • Verifying references is a basic responsibility of researchers, and failure to do so is a sign of laziness or incompetence.
  • The use of AI in research can be convenient, but it is not an excuse for sloppy research practices, and researchers must take responsibility for ensuring the accuracy of their citations.
  • The policy may be effective in preventing fake references, but it may also have unintended consequences, such as discouraging researchers from using AI tools or submitting to ArXiv.