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English(EN) CC-Mediation: Evaluating Large Language Models for Cross-Cultural Conflict Mediation

新基准评估大型语言模型在跨文化冲突调解中的能力

研究人员推出了CC-Mediation,这是一个旨在评估大型语言模型(LLM)在跨文化冲突调解中能力的新基准。该基准包含1,661个基于跨文化敏感性发展模型(DMIS)的对话,涉及具有文化特性的冲突和调解干预。为了评估LLM的性能,提出了两个新指标:轨迹AUC和有符号Wasserstein-1距离,分别用于衡量跨文化立场转变的持久性和幅度。初步研究结果表明,当前的LLM在确定干预的适当时机方面存在困难,并且在调解策略上表现出失败,这通常是由于后期提取问题而非知识不足。 AI

影响 该基准可以推动LLM在处理复杂、具有文化细微差别的互动方面的能力得到提升,从而可能实现更有效的AI辅助冲突解决。

排序理由 该集群描述了一篇介绍LLM新基准和评估指标的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新基准评估大型语言模型在跨文化冲突调解中的能力

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该集群描述了一篇介绍LLM新基准和评估指标的学术论文。[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) · Suhyun Lee, Wenxuan Zhang, W. Quin Yow, Yang Deng ·

    CC-Mediation:评估大型语言模型在跨文化冲突调解中的应用

    arXiv:2609.04855v1 Announce Type: cross Abstract: Cross-cultural mediation by large language models (LLMs) requires deciding both when to intervene and how to respond in culturally grounded conflicts. Progress on this problem has been limited by the lack of (1) mediation datasets…