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English(EN) LexPilot: Benchmarking the Proactive Interaction Ability of Legal LLMs with Laypeople in Chinese Civil Case Consultation

新的LexPilot基准测试显示法律大语言模型在主动用户交互方面存在困难

一项名为LexPilot的新基准测试已被开发出来,用于评估法律大语言模型(LLMs)在与普通用户就中国民事案件进行咨询时的主动交互能力。研究人员发现,当前的大语言模型在面对信息不明确的查询时,常常提供无益的回答,未能引导用户提供必要的细节。LexPilot由432份真实中国民事判决书构建而成,将主动交互与索赔级别判决预测联系起来,揭示了在缺乏足够案件背景信息的情况下,大语言模型的性能会显著下降。 AI

影响 强调了需要更以用户为中心的法律人工智能,以改善普通用户的咨询体验和下游案件预测。

排序理由 该集群包含一篇介绍用于评估大语言模型能力的新的基准测试的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新的LexPilot基准测试显示法律大语言模型在主动用户交互方面存在困难

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该集群包含一篇介绍用于评估大语言模型能力的新的基准测试的学术论文。[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) · Wenbin Zhang, ShangZhan Li, Bingxiang He, Ye He, Yuxin Zhou, Muzhen Cai, Qi Shi, Wanxiang Che ·

    LexPilot:基准测试法律大语言模型与普通用户在中国民事案件咨询中的主动交互能力

    arXiv:2610.23141v1 Announce Type: new Abstract: Large Language Models (LLMs) have greatly assisted legal professionals. However, our empirical studies reveal that, when faced with underspecified consultations from non-experts, current LLMs often produce irresponsible responses wi…