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English(EN) How Well Do LLMs Perform in Peer Review? Evidence from Finance and Accounting

研究发现:LLM可检查研究的正确性但无法判断其重要性

一篇新发表在arXiv上的研究探讨了大型语言模型(LLM)在金融和会计期刊同行评审过程中的有效性。研究人员发现,GPT-4o和GPT-5能够准确评估研究论文的正确性和表述,模型评分较高的论文发表的可能性高出44%。然而,这些模型在判断研究的原创性或重要性方面表现不出能力,这表明虽然LLM可以验证研究的技术准确性,但人类判断在评估其影响方面仍然至关重要。 AI

影响 LLM可以协助研究的技术评审,但人类判断在评估原创性和重要性方面仍然必不可少。

排序理由 该集群包含一篇详细介绍LLM能力研究结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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研究发现:LLM可检查研究的正确性但无法判断其重要性

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该集群包含一篇详细介绍LLM能力研究结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Hai Lu, Yichen Luo, Luping Yu ·

    大型语言模型在同行评审中的表现如何?来自金融和会计领域的证据

    arXiv:2610.18435v1 Announce Type: cross Abstract: Referees increasingly use large language models (LLMs), while finance and accounting journals disagree about whether to allow it. We ask which part of a referee's job the models can do. GPT-4o, whose training data end before the 2…