To enhance language models' cultural awareness, we design a generalizable pipeline to construct cultural knowledge bases from different online communities on a massive scale. With the pipeline, we construct CultureBank, a knowledge base built upon users' self-narratives with 12K cultural descriptors sourced from TikTok and 11K from Reddit. Unlike previous cultural knowledge resources, CultureBank contains diverse views on cultural descriptors to allow flexible interpretation of cultural knowledge, and contextualized cultural scenarios to help grounded evaluation. With CultureBank, we evaluate different LLMs' cultural awareness, and identify areas for improvement. We also fine-tune a language model on CultureBank: experiments show that it achieves better performances on two downstream cultural tasks in a zero-shot setting. Finally, we offer recommendations based on our findings for future culturally aware language technologies. The project page is https://culturebank.github.io . The code and model is at https://github.com/SALT-NLP/CultureBank . The released CultureBank dataset is at https://huggingface.co/datasets/SALT-NLP/CultureBank .

中文翻译：

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CultureBank：一个在线社区驱动的知识库，旨在实现文化意识语言技术

为了增强语言模型的文化意识，我们设计了一个通用的管道来大规模构建来自不同在线社区的文化知识库。通过该管道，我们构建了 CultureBank，这是一个基于用户自我叙述的知识库，其中包含来自 TikTok 的 12K 文化描述符和来自 Reddit 的 11K 文化描述符。与以往的文化知识资源不同，CultureBank包含了多种文化描述符观点，可以灵活解读文化知识，并提供情境化的文化场景，帮助进行落地评估。通过 CultureBank，我们评估不同法学硕士的文化意识，并找出需要改进的领域。我们还在 CultureBank 上微调了语言模型：实验表明，它在零样本设置中在两个下游文化任务上取得了更好的性能。最后，我们根据我们的发现为未来的文化意识语言技术提供建议。项目页面为 https://culturebank.github.io 。代码和模型位于 https://github.com/SALT-NLP/CultureBank 。已发布的 CultureBank 数据集位于 https://huggingface.co/datasets/SALT-NLP/CultureBank 。