Aligned but Flattened: Analyzing the Trade-off between Cultural Alignment and Diversity in LLMs
Cultural fine-tuning has become the de facto paradigm for building culture-aware large language models (LLMs), yet existing optimization exclusively for alignment scores provides an incomplete portrait of cultural fidelity by systematically obscuring inherent cultural diversity. This unidimensional evaluation lens prompts a fundamental question: do models genuinely perceive distinct cultural nuances, or do they merely memorize dominant cultural values? To address this, we propose a synergistic evaluation framework that jointly formalizes cultural alignment and diversity. Through extensive benchmarking of six mainstream LLMs on the World Values Survey, this framework uncovers a systematic ...
| Authors | Jingshen Zhang, Shaoyang Xu, Wenxuan Zhang |
|---|---|
| Primary category | cs.SI |
| Published | 1 September 2026 |
| Last updated at source | 1 September 2026 |
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