arXiv:2510. 08543v2 Announce Type: replace-cross Abstract: As Video Large Language Models (VideoLLMs) are deployed globally, it is important to assess their ability to reason across cultural contexts.
By Nikhil Reddy Varimalla, Yunfei Xu, Meng Fan Wang, Arkadiy Saakyan, Smaranda Muresan
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.
By Candida M. Greco, Lucio La Cava, Andrea Tagarelli
arXiv:2607. 26348v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as synthetic users, stand-ins for human respondents whose simulated answers feed product, policy, and market decisions.
By Zihan Chen, Di Zhu, Lei Nico Zheng
arXiv:2606. 19640v1 Announce Type: cross Abstract: AI and large language models (LLMs) have emerged as promising tools to address global mental health challenges.
By Yunkai Xu, Saeed Abdullah
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
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
arXiv:2606. 26982v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into mental health support tools and other psychologically sensitive conversational applications.
By Abla Bedoui, Ashley L. Greene, Mohammed Cherkaoui
arXiv:2606. 08483v1 Announce Type: new Abstract: Background: Consumer-facing large language models are now a common source of health information, and they interpret and personalize responses rather than retrieve them.
By Rahul Gorijavolu, Kaushik Madapati, Pritika Vig, Rawan Abulibdeh, Nikhil Jaiswal, Mahri Kadyrova, Zeamanuel Hailu Tesfaye, Charles Senteio, Paula Maurutto, Leo Anthony Celi
arXiv:2606. 00369v1 Announce Type: cross Abstract: Safe global deployment of AI models requires alignment with human values that vary across cultures.
By Arkadiy Saakyan, Charvi Rastogi, Lora Aroyo
arXiv:2606. 07311v1 Announce Type: cross Abstract: As video generation models like Veo 3.
By Anku Rani, Wei Dai, Shravan Nayak, Pattie Maes, Mahdi M. Kalayeh, Paul Pu Liang
arXiv:2601. 14063v2 Announce Type: replace-cross Abstract: Cross-cultural competence in large language models (LLMs) requires understanding and adapting Culture-Specific Items (CSIs) across varying cultural contexts.
By Mohsinul Kabir, Tasnim Ahmed, Md Mezbaur Rahman, Shaoxiong Ji, Hassan Alhuzali, Yuechen Jiang, Jimin Huang, Sophia Ananiadou
arXiv:2605. 28543v2 Announce Type: replace Abstract: LLMs often default to equal treatment across cultural groups, even though context warrants differentiation: this is a lack of difference awareness.
By Avrile Floro, Luca Benedetto