迈向社区价值观和常识的文化智能与价值观推理质量基准
Towards A Cultural Intelligence and Values Inferences Quality Benchmark for Community Values and Common Knowledge
AI总结：
本文提出CIVIQ基准，旨在通过社区价值观和常识对齐提升文化智能，填补美国文化多样性下的评估空白。
摘要：
大型语言模型（LLMs）已作为一种强大的技术出现，因此在软件工程团队中得到了广泛应用。大多数情况下，LLMs被设计为
英文摘要：
Large language models (LLMs) have emerged as a powerful technology, and thus, we have seen widespread adoption and use on software engineering teams. Most often, LLMs are designed as "general purpose" technologies meant to represent the general population. Unfortunately, this often means alignment with predominantly Western Caucasian narratives and misalignment with other cultures and populations that engage in collaborative innovation. In response to this misalignment, there have been recent efforts centered on the development of "culturally-informed" LLMs, such as ChatBlackGPT, that are capable of better aligning with historically marginalized experiences and perspectives. Despite this progress, there has been little effort aimed at supporting our ability to develop and evaluate culturally-informed LLMs. A recent effort proposed an approach for developing a national alignment benchmark that emphasizes alignment with national social values and common knowledge. However, given the range of cultural identities present in the United States (U.S.), a national alignment benchmark is an ineffective goal for broader representation. To help fill this gap in this US context, we propose a replication study that translates the process used to develop KorNAT, a Korean National LLM alignment benchmark, to develop CIVIQ, a Cultural Intelligence and Values Inference Quality benchmark centered on alignment with community social values and common knowledge. Our work provides a critical foundation for research and development aimed at cultural alignment of AI technologies in practice.
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。
