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English(EN) FirmCORe: A Benchmark for Structured Reasoning about Inter-Firm Collaboration Opportunities

新的FirmCORe基准测试LLM在企业间协作推理能力

研究人员推出了一项新的基准FirmCORe,旨在评估大型语言模型(LLM)识别和推理公司之间协作机会的能力。该基准包含2,805个已标记的公司对,不仅评估潜在协作的检测,还评估其强度、类型和角色方向。使用各种LLM进行的初步实验表明,虽然模型可以以74.51%的宏F1分数检测到机会,但在识别具体的协作细节时,其性能会显著下降,在所有输出字段上的精确匹配率仅为61.57%。该基准还包括并行的中文和英文评估集,以分析语言敏感性。 AI

影响 该基准有望推动LLM在理解复杂商业关系和促进战略伙伴关系方面的能力提升。

排序理由 该项目描述了一个用于评估LLM能力的新学术基准。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新的FirmCORe基准测试LLM在企业间协作推理能力

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该项目描述了一个用于评估LLM能力的新学术基准。[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) · Tian Du, Tiantong Wu, Yafei Wang, Mengyu Liu, Xingyan Chen, Mu Wang ·

    FirmCORe:一个关于企业间协作机会的结构化推理基准

    arXiv:2609.17128v1 Announce Type: new Abstract: Comprehensive structured data on inter-firm relationships is often scarce or inaccessible because many relationships are privately negotiated, selectively disclosed, and fragmented across proprietary databases. This scarcity hinders…