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English(EN) Different Demographic Cues Yield Inconsistent Conclusions About LLM Personalization and Bias

大型语言模型人口统计提示显示出偏见和不一致性

新的研究表明,使用社会人口统计提示与大型语言模型(LLMs)来使其判断与特定人群保持一致,可能会导致意想不到的后果。一项研究发现,未经人口统计条件约束的模型倾向于偏袒多数群体的判断,并且在敏感环境中,约束条件可能不成比例地使预测偏离少数群体。另一篇论文强调,不同的社会人口统计线索,例如姓名,可能会在大型语言模型的个性化和偏见方面产生不一致的结果,这表明模型对语言信号而非稳定的社会人口统计类别做出反应。两项研究都呼吁在使用大型语言模型的人口统计信息时要谨慎并采用更细致的评估方法。 AI

影响 强调了大型语言模型对人口统计线索的响应中潜在的偏见和不一致性,敦促在应用中要谨慎。

排序理由 两篇在arXiv上发表的学术论文,讨论了大型语言模型在人口统计线索下的行为。

在 arXiv cs.CL 阅读 →

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大型语言模型人口统计提示显示出偏见和不一致性

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两篇在arXiv上发表的学术论文,讨论了大型语言模型在人口统计线索下的行为。
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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Daniela Occhipinti, Andrea Piergentili, Marco Guerini ·

    LLM作为人口统计学:社会人口统计学提示帮助了谁,又伤害了谁

    arXiv:2609.00222v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as judges for subjective tasks, where annotators disagree and the relevant question is not only how accurate a judge is, but whose judgments it reproduces. Sociodemographic promptin…

  2. arXiv cs.CL TIER_1 English(EN) · Manuel Tonneau, Neil K. R. Sehgal, Niyati Malhotra, Sharif Kazemi, Victor Orozco-Olvera, Ana Mar\'ia Mu\~noz Boudet, Lakshmi Subramanian, Samuel P. Fraiberger, Sharath Chandra Guntuku, Valentin Hofmann ·

    不同的人口统计线索导致对大型语言模型个性化和偏见的结论不一致

    arXiv:2601.18486v3 Announce Type: replace Abstract: Demographic cue-based evaluation is widely used to study how large language models (LLMs) adapt their responses to signaled demographic attributes within and across groups. This approach typically relies on a single cue (e.g., n…