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arxiv: 2410.01811 · v1 · pith:D4BPQ6RFnew · submitted 2024-09-14 · 💻 cs.CY · cs.AI· cs.CL

Evaluating Cultural Awareness of LLMs for Yoruba, Malayalam, and English

classification 💻 cs.CY cs.AIcs.CL
keywords culturalllmsmalayalamregionalyorubaalthoughawarenessenglish
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Although LLMs have been extremely effective in a large number of complex tasks, their understanding and functionality for regional languages and cultures are not well studied. In this paper, we explore the ability of various LLMs to comprehend the cultural aspects of two regional languages: Malayalam (state of Kerala, India) and Yoruba (West Africa). Using Hofstede's six cultural dimensions: Power Distance (PDI), Individualism (IDV), Motivation towards Achievement and Success (MAS), Uncertainty Avoidance (UAV), Long Term Orientation (LTO), and Indulgence (IVR), we quantify the cultural awareness of LLM-based responses. We demonstrate that although LLMs show a high cultural similarity for English, they fail to capture the cultural nuances across these 6 metrics for Malayalam and Yoruba. We also highlight the need for large-scale regional language LLM training with culturally enriched datasets. This will have huge implications for enhancing the user experience of chat-based LLMs and also improving the validity of large-scale LLM agent-based market research.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Cultural Authenticity: Comparing LLM Cultural Representations to Native Human Expectations

    cs.CL 2026-04 unverdicted novelty 6.0

    LLMs display Western-centric cultural representations that align poorly with native priorities in non-Western countries and share highly correlated error patterns.