Having Beer after Prayer? Measuring Cultural Bias in Large Language Models

arXiv:2305.14456v3 Announce Type: replace-cross
Abstract: As the reach of large language models (LMs) expands globally, their ability to cater to diverse cultural contexts becomes crucial. Despite advancements in multilingual capabilities, models are not designed with appropriate cultural nuances. In this paper, we show that multilingual and Arabic monolingual LMs exhibit bias towards entities associated with Western culture. We introduce CAMeL, a novel resource of 628 naturally-occurring prompts and 20,368 entities spanning eight types that contrast Arab and Western cultures. CAMeL …

arxiv beer bias cs.ai cs.cl cs.lg language language models large language large language models measuring type