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AI in scientific peer review: A survey and a security analysis

By PulseAugur Editorial · [3 sources] ·

Two recent arXiv papers explore the integration of AI into the scientific peer review process, highlighting both its potential benefits and significant risks. One survey synthesizes current techniques for AI-assisted peer review generation, rebuttal assistance, and evaluation methods, aiming to guide practical implementation. The other paper focuses on the security and reliability of AI referees, detailing various attack vectors and experimental findings that reveal vulnerabilities such as susceptibility to prompt injections and biases, questioning the trustworthiness of AI in scientific evaluation. AI

IMPACT AI's role in scientific peer review is under scrutiny, with new research detailing vulnerabilities and potential mitigations for AI referees.

RANK_REASON Two academic papers published on arXiv discuss the use of AI in scientific peer review.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

AI in scientific peer review: A survey and a security analysis

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COVERAGE [3]

  1. arXiv cs.AI TIER_1 English(EN) · Sihong Wu, Owen Jiang, Yilun Zhao, Tiansheng Hu, Yiling Ma, Kaiyan Zhang, Manasi Patwardhan, Arman Cohan ·

    Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future

    arXiv:2604.27924v1 Announce Type: cross Abstract: Peer review is a multi-stage process involving reviews, rebuttals, meta-reviews, final decisions, and subsequent manuscript revisions. Recent advances in large language models (LLMs) have motivated methods that assist or automate …

  2. arXiv cs.CL TIER_1 English(EN) · Arman Cohan ·

    Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future

    Peer review is a multi-stage process involving reviews, rebuttals, meta-reviews, final decisions, and subsequent manuscript revisions. Recent advances in large language models (LLMs) have motivated methods that assist or automate different stages of this pipeline. In this survey,…

  3. arXiv cs.AI TIER_1 English(EN) · Jialiang Wang, Yuchen Liu, Hang Xu, Kaichun Hu, Shimin Di, Wangze Ni, Linan Yue, Min-Ling Zhang, Kui Ren, Lei Chen ·

    When AI reviews science: Can we trust the referee?

    arXiv:2604.23593v1 Announce Type: new Abstract: The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the same time, modern large language models (LLMs) offer impressive capabilities in s…

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