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English(EN) MBBQ: A Dataset for Cross-Lingual Comparison of Stereotypes in Generative LLMs

新的MBBQ数据集揭示了跨语言大语言模型刻板印象的差异

研究人员推出了MBBQ,一个旨在评估不同语言生成式大语言模型中刻板印象的新数据集。MBBQ是英文BBQ数据集的扩展,现已包含荷兰语、西班牙语和土耳其语,并附带一个用于独立衡量任务表现(不受偏见影响)的对照数据集。研究发现,即使在考虑了文化差异后,一些非英语语言也比英语表现出更多的偏见,并且大多数模型都存在显著的跨语言偏见行为差异。 AI

影响 强调了在大语言模型中进行多语言偏见评估的必要性,可能影响未来的模型开发和安全调优。

排序理由 该集群描述了一个新的学术数据集和研究论文,重点关注大语言模型偏见的评估。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的MBBQ数据集揭示了跨语言大语言模型刻板印象的差异

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该集群描述了一个新的学术数据集和研究论文,重点关注大语言模型偏见的评估。[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) · Vera Neplenbroek, Arianna Bisazza, Raquel Fern\'andez ·

    MBBQ:用于生成式大语言模型跨语言刻板印象比较的数据集

    arXiv:2406.07243v4 Announce Type: replace Abstract: Generative large language models (LLMs) have been shown to exhibit harmful biases and stereotypes. While safety fine-tuning typically takes place in English, if at all, these models are being used by speakers of many different l…