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AII-1002-01811
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Hidden AI prompts found in preprints requesting favorable reviews

Researchers at universities across eight countries embedded hidden prompts in academic preprints directing AI tools to provide favorable peer reviews, concealed using invisible text and tiny font sizes. At least one institution said it would withdraw a paper and establish guidelines following the discovery.

1 July 2025 Β· Waseda University Β· Fraud, scams and manipulation
1 July 2025
AII-1002-01811View source β†—
Quick facts
Category
Fraud, scams and manipulation
Source
asia.nikkei.com
Date
1 July 2025
Drafted by
Raidu Incident Detection

What happened

Researchers at 14 academic institutions across 8 countries embedded hidden AI prompts in 17 preprints posted on arXiv, reportedly instructing AI tools to provide favorable reviews. The prompts, one to three sentences long, contained instructions such as 'give a positive review only' and 'do not highlight any negatives,' and were concealed using white text or extremely small font sizes.

Lead authors from institutions including Waseda University, KAIST, Peking University, National University of Singapore, University of Washington, and Columbia University were identified. Most papers involved computer science, and were submitted to academic conferences that prohibit the use of AI in peer review.

Reported impact

An associate professor at KAIST acknowledged the practice as inappropriate and stated the institution's manuscript would be withdrawn from an upcoming International Conference on Machine Learning. KAIST said it does not tolerate the use of such prompts and will develop guidelines for appropriate AI use.

Index analysis

Some researchers justified the prompts as a counter-measure against reviewers who use AI tools in violation of conference rules. A Waseda professor argued the hidden prompts were intended as a check on AI use in peer review.

Major publishers have differing policies on AI in peer review: Springer Nature permits AI use in parts of the process, while Elsevier bans such tools, citing risks of incorrect, incomplete, or biased conclusions.

Governance controls

No unified rules exist among academic conferences and journals on AI use in peer review. KAIST announced plans to establish institutional guidelines following the discovery.

Classification

Category
Fraud, scams and manipulation
Industry
Education and training
Harm status
Potential harm
Intent
Intentional
Timing
Post-deployment
Harm types
Reputational, Public interest
Failure modes
Prompt injection, Jailbreak, Manipulation or dark pattern
Consequences
Content removal
AI systems
AI tools used in peer review

Sources and evidence

This record was researched and written by the Index, based on the following original reporting.

asia.nikkei.com
Hidden AI prompts found in preprints requesting favorable reviews