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English(EN) The Male Abstraction Bias in Internet Culture and Large Language Models

新研究揭示互联网文化和大型语言模型中普遍存在的“男性抽象偏见”

一篇发表在arXiv上的新研究论文探讨了互联网文化和大型语言模型中普遍存在的“男性抽象偏见”。该研究分析了数十亿个单词和数百万张图片,发现在不同语言和测量技术中,抽象概念与男性之间存在持续的关联。这种偏见延伸到语法结构,动词和副词更抽象且带有男性编码,反映了男性特质的刻板印象。研究表明,这种偏见在自由联想任务中会被人类和AI内化和复制,表明它可能是概念空间中一个基本的组织原则。 AI

影响 强调了LLM中潜在的性别偏见,敦促开发人员解决训练数据和模型输出中的抽象性和性别关联问题。

排序理由 发表在arXiv上的研究论文,详细介绍了LLM和互联网文化中偏见的发现。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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新研究揭示互联网文化和大型语言模型中普遍存在的“男性抽象偏见”

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发表在arXiv上的研究论文,详细介绍了LLM和互联网文化中偏见的发现。[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) · Douglas Guilbeault, Bhargav Srinivasa Desikan ·

    互联网文化与大型语言模型中的男性抽象偏见

    arXiv:2611.05730v1 Announce Type: cross Abstract: Two foundational aspects of human cognition, abstractness and gender, are typically examined as separable. Here, we find they are systematically linked throughout the entire space of concepts spanning single (N = 40,000) and multi…