arXiv AI June 4, 2026 By Candida M. Greco, Lucio La Cava, Andrea Tagarelli

Culturally Grounded Personas in Large Language Models: Characterization and Alignment with Socio-Psychological Value Frameworks

arXiv:2601. 22396v2 Announce Type: replace-cross Abstract: Despite the growing utility of Large Language Models (LLMs) for simulating human behavior, the extent to which these synthetic personas accurately reflect world and moral value systems across different cultural conditionings remains uncertain.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jul 29

Personalization, Personas, and Forecasting in Value Alignment

arXiv:2607. 24782v1 Announce Type: new Abstract: LLM behavior may be conditioned by human identity in several ways: they may be asked to adapt to users, role-play populations, or forecast how people would answer value-laden questions.

By James Wedgwood, Pratiksha Thaker, Neil Kale, Virginia Smith

llms safety

arXiv AI

Jul 3

Cross-Cultural Value Attribution in Large Vision-Language Models

arXiv:2604. 09945v2 Announce Type: replace-cross Abstract: The rapid adoption of large vision-language models (LVLMs) in recent years has been accompanied by growing fairness concerns due to their propensity to reinforce harmful societal stereotypes.

By Phillip Howard, Xin Su, Kathleen C. Fraser

llms multimodal safety

arXiv AI

Jun 17

Teaching Values to Machines: Simulating Human-Like Behavior in LLMs

arXiv:2605. 30036v2 Announce Type: replace Abstract: Large Language Models (LLMs) demonstrate a remarkable capacity to adopt different personas and roles; however, it remains unclear whether they can manifest behavior that adheres to a coherent, human-like value structure.

By Asaf Yehudai, Naama Rozen, Ariel Gera

llms safety

arXiv AI

Jun 12

Occupational Prompting Reveals Cultural Bias in Large Language Models

arXiv:2606. 12443v1 Announce Type: cross Abstract: Social roles shape expectations, priorities, and judgments, yet it remains unclear how large language models (LLMs) associate occupational identities with broader cultural value patterns.

By Maksim E. Eren, Andrea Brennen, Ryan C. Barron, Eric Michalak

llms benchmarks safety

arXiv AI

Jul 8

CCBENCH: Assessing LLM Cultural Competence via Implicitly Signaled Norms using Health Queries

arXiv:2607. 05405v1 Announce Type: cross Abstract: To interact with users fairly and without stereotyping, AI models must display cultural competency, i.

By Vasudha Varadarajan, Akhila Yerukola, Mona T. Diab, Maarten Sap

llms benchmarks

Hugging Face Trending Papers

Jul 9

PLURAL: A Global Dataset for Value Alignment

Large language models (LLMs) are used worldwide, yet disproportionately reflect Western values, limiting their ability to represent diverse value systems. We introduce PLURAL, a large-scale, value-focused preference dataset grounded in the Integrated Values Survey (IVS), a nationally representative survey spanning 92 countries.

llms safety

Related stories

Personalization, Personas, and Forecasting in Value Alignment

Cross-Cultural Value Attribution in Large Vision-Language Models

Teaching Values to Machines: Simulating Human-Like Behavior in LLMs

Occupational Prompting Reveals Cultural Bias in Large Language Models

CCBENCH: Assessing LLM Cultural Competence via Implicitly Signaled Norms using Health Queries

PLURAL: A Global Dataset for Value Alignment