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English(EN) When Does Defendant Statement Matter? A Study of Bias and Persuasion in LLM-Simulated Jurors

大型语言模型陪审员根据被告陈述和背景表现出偏见

一项名为 JuryBench 的新基准已被开发出来,用于研究在美国刑事法律案件中,大型语言模型模拟的陪审员如何受到被告陈述的影响。该研究分析了来自 20 个前沿大型语言模型的超过 432,000 个判决,发现情感说服会对感知到的罪责产生负面影响,并且被告与陪审员之间的背景亲和力是量刑的重要因素。意识形态在塑造严重性判断方面也起着重要作用,这既揭示了使用大型语言模型模拟陪审员推理的潜力,也揭示了其风险。 AI

影响 强调了大型语言模型模拟法律决策中存在的潜在偏见,为开发更公平的人工智能系统提供了信息。

排序理由 学术论文,介绍了一个新的基准和对大型语言模型行为的分析。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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大型语言模型陪审员根据被告陈述和背景表现出偏见

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学术论文,介绍了一个新的基准和对大型语言模型行为的分析。[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) · Cho-Ying Wu ·

    被告陈述何时重要?一项关于LLM模拟陪审员偏见与说服力的研究

    arXiv:2609.09887v1 Announce Type: new Abstract: LLMs have been used to simulate human decision-making in professional settings, yet their behaviors in common-law jury trials remain unexplored. We study when and how a defendant's courtroom statement affects LLM-simulated jurors, f…