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Language over Content: Tracing Cultural Understanding in Multilingual Large Language Models

arXiv — cs.LG•Wednesday, November 12, 2025 at 5:00:00 AM
NeutralArtificial Intelligence
The study on large language models (LLMs) emphasizes the critical role of cultural understanding in their application across diverse contexts. Traditional evaluations have often overlooked the underlying mechanisms that influence responses, focusing instead on output performance. This research employs a novel method of measuring activation path overlaps to explore how LLMs process questions differently based on language and cultural context. The findings reveal that responses to same-language, cross-country questions exhibit greater internal path overlap than those to cross-language, same-country questions, underscoring the significance of language-specific patterns. Particularly striking is the case of South Korea and North Korea, where despite linguistic similarities, the models displayed low overlap and high variability in their responses. This suggests that effective communication in multilingual settings requires more than just linguistic proficiency; it necessitates a nuanced und…
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