大型语言模型的文化对齐性研究
Investigating Cultural Alignment of Large Language Models
AI总结：
本文通过模拟社会学调查量化LLMs的文化对齐性，发现主导语言提示和精细多语预训练可提升对齐性，并提出人类学提示方法以改善文化对齐，强调平衡多语言预训练数据的重要性。
摘要：
语言与文化之间错综复杂的关系长期以来一直是语言人类学领域探索的主题。大型语言模型（LLMs）被宣传为集体人类知识的存储库，这引出了一个关键问题：这些模型是否真正囊括了不同文化所采纳的多样化知识？我们的研究表明，这些模型在两个维度上表现出更强的文化对齐性——首先，当以特定文化的主导语言进行提示时；其次，当使用该文化所使用语言的精细混合语料进行预训练时。我们通过模拟社会学调查来量化文化对齐性，将模型回答与真实调查参与者的回答作为参照进行比较。具体而言，我们通过在阿拉伯语和英语中使用不同的预训练数据混合，并以真实受访者的人设和调查问题来提示LLMs，复现了一项在埃及和美国多个地区进行的调查。进一步分析表明，对于代表性不足的人设以及文化敏感话题（例如探究社会价值观的话题），错位现象更加明显。最后，我们引入了人类学提示（Anthropological Prompting），这是一种利用人类学推理来增强文化对齐性的新方法。我们的研究强调了需要更平衡的多语言预训练数据集，以更好地代表人类经验的多样性和不同文化的多元性，这对跨语言迁移这一主题具有诸多启示。
英文摘要：
The intricate relationship between language and culture has long been a subject of exploration within the realm of linguistic anthropology. Large Language Models (LLMs), promoted as repositories of collective human knowledge, raise a pivotal question: do these models genuinely encapsulate the diverse knowledge adopted by different cultures? Our study reveals that these models demonstrate greater cultural alignment along two dimensions -- firstly, when prompted with the dominant language of a specific culture, and secondly, when pretrained with a refined mixture of languages employed by that culture. We quantify cultural alignment by simulating sociological surveys, comparing model responses to those of actual survey participants as references. Specifically, we replicate a survey conducted in various regions of Egypt and the United States through prompting LLMs with different pretraining data mixtures in both Arabic and English with the personas of the real respondents and the survey questions. Further analysis reveals that misalignment becomes more pronounced for underrepresented personas and for culturally sensitive topics, such as those probing social values. Finally, we introduce Anthropological Prompting, a novel method leveraging anthropological reasoning to enhance cultural alignment. Our study emphasizes the necessity for a more balanced multilingual pretraining dataset to better represent the diversity of human experience and the plurality of different cultures with many implications on the topic of cross-lingual transfer.
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