mlsanityData to 14 Oct 2026

Can LLMs Express Personality Across Cultures? Introducing CulturalPersonas for Evaluating Trait Alignment

arXiv 2506.05670 ↗First posted 6 Jun 2025cs.CLcited by 9

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Abstract (arXiv)

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 CulturalPersonas, 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 three LLMs, using both multiple-choice and open-ended response formats. Our results show that 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 modulated 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.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 11 of its 52 references that are in the map. First posted on arXiv 6 Jun 2025.

Builds on

11 of 52 references.

References · 11

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  3. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,455
  4. 2023PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traitscited by 234
  5. 2024Do LLMs Have Distinct and Consistent Personality? TRAIT: Personality Testset designed for LLMs with Psychometricscited by 59
  6. 2024BIG5-CHAT: Shaping LLM Personalities Through Training on Human-Grounded Datacited by 50
  7. 2024Do Generative AI Models Output Harm while Representing Non-Western Cultures: Evidence from A Community-Centered Approachcited by 26
  8. 2023Editing Personality for Large Language Modelscited by 22
  9. 2023Controlling Personality Style in Dialogue with Zero-Shot Prompt-Based Learningcited by 14
  10. 2024Multilingual Retrieval Augmented Generation for Culturally-Sensitive Tasks: A Benchmark for Cross-lingual Robustnesscited by 14
  11. 2024PersonalityChat: Conversation Distillation for Personalized Dialog Modeling with Facts and Traitscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 8.

9 papers.

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  1. 2025Evaluating LLM Alignment on Personality Inference from Real-World Interview Data
  2. 2026CuBEs: Culturally-Situated Behavioral Evaluations and the Limitations of Culture-Blind LLM Judges
  3. 2025Humanizing LLMs: A Survey of Psychological Measurements with Tools, Datasets, and Human-Agent Applications
  4. 2025Beyond BFI: The CSI for Enhanced Reliability and Validity in Evaluating LLM Personality Traits
  5. 2026To Generate or Discriminate? Methodological Considerations for Measuring Cultural Alignment in LLMs
  6. 2026Can Persona-Prompted LLMs Emulate Subgroup Values? An Empirical Analysis of Generalisability and Fairness in Cultural Alignment
  7. 2025Can LLMs Infer Personality from Real World Conversations?
  8. 2024Navigating the Cultural Kaleidoscope: A Hitchhiker's Guide to Sensitivity in Large Language Models