EMNLP Findings2025
Can LLMs Express Personality Across Cultures? Introducing CulturalPersonas for Evaluating Trait Alignment
Priyanka Dey, Aayush Bothra, Yugal Khanter, Jieyu Zhao, Emilio Ferrara
Abstract
As LLMs become central to interactive applications, ranging from tutoring to mental health, the ability to express personality in culturally appropriate ways is increasingly important. While recent works have explored personality evaluation of LLMs, they largely overlook the interplay between culture and personality. To address this, we introduce Cul-turalPersonas, the first large-scale benchmark with human validation for evaluating LLMs' personality expression in culturally grounded, behaviorally rich contexts. Our dataset spans 3,000 scenario-based questions across six diverse countries, designed to elicit personality through everyday scenarios rooted in local values. We evaluate how closely three models' personality distributions align to real human populations through two evaluation settings: multiple-choice and open-ended response formats. Our results show-CulturalPersonas improves alignment with country-specific human personality distributions (over a 20% reduction in Wasserstein distance across models and countries) and elicits more expressive, culturally coherent outputs compared to existing benchmarks. CulturalPersonas surfaces meaningful modulate trait outputs in response to culturally grounded prompts, offering new directions for aligning LLMs to global norms of behavior. By bridging personality expression and cultural nuance, we envision that CulturalPersonas will pave the way for more socially intelligent and globally adaptive LLMs. Datasets and code are available at: https://github.com/limenlp/CulturalPersonas.
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Cited by top-tier papers1
Builds on4
- Evaluating and Inducing Personality in Pre-trained Language ModelsGuangyuan Jiang, Manjie Xu, Song-Chun Zhu, Wenjuan Han et al.NeurIPS 2023 · 192 citations
- Faithful Persona-based Conversational Dataset Generation with Large Language ModelsPegah Jandaghi, XiangHai Sheng, Xinyi Bai, Jay Pujara et al.ACL Findings 2024 · 10 citations
- Multilingual Retrieval Augmented Generation for Culturally-Sensitive Tasks: A Benchmark for Cross-lingual RobustnessBryan Li, Fiona Luo, Samar Haider, Adwait Agashe et al.ACL Findings 2025 · 3 citations
- Neuron based Personality Trait Induction in Large Language ModelsJia Deng, Tianyi Tang, Yanbin Yin, Wenhao Yang et al.ICLR 2025
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