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English(EN) Same-Number Citation Swaps: Stress-Testing Jev as a Financial Evidence Judge

新方法对LLM进行压力测试以确保财务证据引用的准确性

研究人员开发了一种方法来压力测试大型语言模型(LLM),例如GPT-4.1 mini,以评估它们正确引用财务证据的能力。该研究关注一个问题,即LLM可能产生数值上正确的计算,但引用了错误的财务角色或来源。通过在具有相同数字的单元格之间替换引用,研究人员分离了LLM的角色识别能力,揭示了检测不正确引用与支持有效引用之间的权衡。该评估框架旨在使基于LLM的财务助手能够独立评估数值正确性、引用角色支持和接受结果。 AI

影响 这项研究通过提高LLM准确引用证据的能力,可能带来更可靠的基于LLM的财务分析工具。

排序理由 该集群包含一篇详细介绍LLM新评估方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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新方法对LLM进行压力测试以确保财务证据引用的准确性

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该集群包含一篇详细介绍LLM新评估方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Chuhong Xu (Sofia University), Bo Su (Indiana University), Ziyao Chen (University of California, San Diego), Ruiyang Xu (Northeastern University), Shimeng Dai (Michigan State University), Xinyu Qiu (Northeastern University) ·

    同号引用互换:压力测试 Jev 作为金融证据裁判

    arXiv:2610.08675v1 Announce Type: new Abstract: Financial reports repeat values across periods, metrics and accounting lines, allowing an LLM-generated calculation to be numerically correct while citing the wrong financial role. We evaluate what probabilistic evidence verificatio…