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arXiv 2411.00860cs.CLcs.CV

语言模型中的文化意识综述:文本及更多模态

Survey of Cultural Awareness in Language Models: Text and Beyond

University of Copenhagen(哥本哈根大学);KAIST(韩国科学技术院)

Siddhesh Pawar, Junyeong Park, Jiho Jin, Arnav Arora, Junho Myung, Srishti Yadav, Faiz Ghifari Haznitrama, Inhwa Song, Alice Oh, Isabelle Augenstein

AI总结:

该综述以人类学、心理学的文化定义为基础,界定大语言模型的文化意识,梳理文本及多模态大模型文化融入的数据集构建、下游任务策略、基准测试方法,讨论相关伦理与跨领域作用并提出未来研究方向。

摘要:

大语言模型(LLMs)在聊天机器人、虚拟助手等各类应用中的大规模部署,要求其对用户具备文化敏感性以确保包容性。文化在心理学和人类学中已有广泛研究,近期让LLMs更具文化包容性的研究激增,这类研究超越多语言范畴,且以心理学和人类学的研究成果为基础。本文综述了将文化意识融入文本型及多模态LLMs的相关研究工作。我们首先以人类学和心理学中的文化定义为出发点,界定了LLMs中文化意识的定义。随后,我们考察了构建跨文化数据集所采用的方法、下游任务中的文化融入策略,以及用于基准测试LLMs文化意识的方法体系。此外,我们还讨论了文化对齐的伦理影响、人机交互在推动LLMs文化融入中的作用,以及文化对齐在推动社会科学研究中的作用。最后,我们基于对文献空白的研究发现,为未来研究指明了方向。

英文摘要:

Large-scale deployment of large language models (LLMs) in various applications, such as chatbots and virtual assistants, requires LLMs to be culturally sensitive to the user to ensure inclusivity. Culture has been widely studied in psychology and anthropology, and there has been a recent surge in research on making LLMs more culturally inclusive in LLMs that goes beyond multilinguality and builds on findings from psychology and anthropology. In this paper, we survey efforts towards incorporating cultural awareness into text-based and multimodal LLMs. We start by defining cultural awareness in LLMs, taking the definitions of culture from anthropology and psychology as a point of departure. We then examine methodologies adopted for creating cross-cultural datasets, strategies for cultural inclusion in downstream tasks, and methodologies that have been used for benchmarking cultural awareness in LLMs. Further, we discuss the ethical implications of cultural alignment, the role of Human-Computer Interaction in driving cultural inclusion in LLMs, and the role of cultural alignment in driving social science research. We finally provide pointers to future research based on our findings about gaps in the literature.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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