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As the scaling of Large Language Models (LLMs) has dramatically enhancedtheir capabilities, there has been a growing focus on the alignment problem toensure their responsible and ethical use. While existing alignment effortspredominantly concentrate on universal values such as the HHH principle, theaspect of culture, which is inherently pluralistic and diverse, has notreceived adequate attention. This work introduces a new benchmark, CDEval,aimed at evaluating the cultural dimensions of LLMs. CDEval is constructed byincorporating both GPT-4's automated generation and human verification,covering six cultural dimensions across seven domains. Our comprehensiveexperiments provide intriguing insights into the culture of mainstream LLMs,highlighting both consistencies and variations across different dimensions anddomains. The findings underscore the importance of integrating culturalconsiderations in LLM development, particularly for applications in diversecultural settings. Through CDEval, we aim to broaden the horizon of LLMalignment research by including cultural dimensions, thus providing a moreholistic framework for the future development and evaluation of LLMs. Thisbenchmark serves as a valuable resource for cultural studies in LLMs, pavingthe way for more culturally aware and sensitive models.

CDEval: A Benchmark for Measuring the Cultural Dimensions of Large Language Models