As large language models (LLMs) become increasingly accessible in many countries, it is essential to align them to serve pluralistic human values across cultures. However, pluralistic culture alignment in LLMs remain an open problem. In this paper, we propose CultureSPA, a Self-Pluralising Culture Alignment framework that allows LLMs to simultaneously align to pluralistic cultures. The framework first generates questions on various culture topics, then yields LLM outputs in response to these generated questions under both culture-aware and culture-unaware settings. By comparing culture-aware/unaware outputs, we are able to detect and collect culture-related instances. These instances are employed to fine-tune LLMs to serve pluralistic cultures in either a culture-joint or culture-specific way. Extensive experiments demonstrate that CultureSPA significantly improves the alignment of LLMs to diverse cultures without compromising general abilities. And further improvements can be achieved if CultureSPA is combined with advanced prompt engineering techniques. Comparisons between culture-joint and culture-specific tuning strategies, along with variations in data quality and quantity, illustrate the robustness of our method. We also explore the mechanisms underlying CultureSPA and the relations between different cultures it reflects.
The Curious Case of Curiosity across Human Cultures and LLMs
University of Michigan - Ann Arbor（密歇根大学安阿伯分校）；University of Toronto（多伦多大学）；Vector Institute（向量研究所）；MPI for Intelligent Systems, Tubingen, Germany（图宾根德国智能系统研究所）
DIWALI: Diversity and Inclusivity aWare cuLture specific Items for India: Dataset and Assessment of LLMs for Cultural Text Adaptation in Indian Context
Natural Language and Information Processing Lab (NLIP) Indian Institute of Technology Hyderabad（自然语言与信息处理实验室（NLIP）印度理工学院海得拉巴）
CLARIN-PT-LDB: An Open LLM Leaderboard for Portuguese to assess Language, Culture and Civility
University of Lisbon NLX—Grupo de Fala e Linguagem Natural, Departmento de Informática Faculdade de Ciências, Campo Grande, 1749-016 Lisboa, Portugal（里斯本大学 NLX—语言与语言自然组，计算机学院，Campo Grande, 1749-016里斯本，葡萄牙）
Evaluating and Improving Cultural Awareness of Reward Models for LLM Alignment
Institute of Computing and Intelligence, Harbin Institute of Technology, Shenzhen, China（计算与智能研究所，哈尔滨工业大学，深圳，中国）；Peng Cheng Laboratory, Shenzhen, China（鹏城实验室，深圳，中国）
Worlds Within Words: Translating Culture in Ancient Chinese Texts with Multi-Agent Coordination
NLP2 CT Lab, Department of Computer and Information Science, University of Macau（澳门大学自然语言处理与计算机实验室，计算机与信息科学系）；Institute of International Language Services Studies, Macau Millennium College（澳门 millennium 学院国际语言服务研究学院）
Prompt Programming for Cultural Bias and Alignment of Large Language Models
Information Systems and Modeling, Los Alamos National Laboratory（信息系统与建模，洛斯阿拉莫斯国家实验室）；Advanced Research in Cyber Systems, Los Alamos National Laboratory（网络安全系统高级研究，洛斯阿拉莫斯国家实验室）；Center for National Security and International Studies（国家安全与国际研究中心）；Analytics Division, Los Alamos National Laboratory（分析部门，洛斯阿拉莫斯国家实验室）
CulturePark: Boosting Cross-cultural Understanding in Large Language Models
Institute of Software, CAS（中国科学院软件研究所）；Idiap Research Institute（Idiap研究所）；Westlake University（西湖大学）；Squirrel AI（松鼠AI）；Microsoft Research（微软研究院）；William & Mary（威廉玛丽学院）
AI shares emotion with humans across languages and cultures
University of Science and Technology of China（中国科学技术大学）；Peking University（北京大学）；Tsinghua University（清华大学）；Beijing Normal University（北京师范大学）；The Hong Kong Polytechnic University（香港理工大学）；The PolyU-Hangzhou Technology and Innovation Research Institute（香港理工大学杭州科技创新研究院）；Changping Laboratory（昌平实验室）
Beyond Instrumental and Substitutive Paradigms: Introducing Machine Culture as an Emergent Phenomenon in Large Language Models
Institute of Neuroscience, Chinese Academy of Sciences（中国科学院神经科学研究所）；University of Cambridge（剑桥大学）；Chinese University of Hong Kong（香港中文大学）；Institute of Public Opinion Survey, Hong Kong SAR（香港特别行政区民意调查研究所）；Tsinghua University（清华大学）
MCEval: A Dynamic Framework for Fair Multilingual Cultural Evaluation of LLMs
Zhejiang University（浙江大学）；School of Engineering, Westlake University（西溪大学工程学院）；Southern University of Science and Technology（南方科技大学）；Institute of Advanced Technology, Westlake Institute for Advanced Study（西溪研究院先进技术研究所）
ALIGN: Word Association Learning for Cultural Alignment in Large Language Models
School of Computing and Information Systems, The University of Melbourne（计算与信息系统学院，墨尔本大学）；Melbourne Data Analytics Platform, The University of Melbourne（墨尔本数据分析平台，墨尔本大学）；Faculty of Information Technology, Monash University（信息技术学院，墨尔本大学）
