Beyond Demographics: Enhancing Cultural Value Survey Simulation with Multi-Stage Personality-Driven Cognitive Reasoning
School of Computer Science and Technology, Wuhan University of Science and Technology（武汉科技大学计算机科学与技术学院）；Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology（湖北省智能信息处理与实时工业系统重点实验室）；Innovation, Policy and Entrepreneurship Thrust, The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州）创新、政策与创业方向）；Tübingen AI Center, University of Tübingen（图宾根大学图宾根人工智能中心）；Department of Computer Science, University of Copenhagen（哥本哈根大学计算机科学系）
Introducing MARK, the Multi-stAge Reasoning frameworK for cultural value survey response simulation, designed to enhance the accuracy, steerability, and interpretability of large language models in this task. The system is inspired by the type dynamics theory in the MBTI psychological framework for personality research. It effectively predicts and utilizes human demographic information for simulation: life-situational stress analysis, group-level personality prediction, and self-weighted cognitive imitation. Experiments on the World Values Survey show that MARK outperforms existing baselines by 10% accuracy and reduces the divergence between model predictions and human preferences. This highlights the potential of our framework to improve zero-shot personalization and help social scientists interpret model predictions.
Large Language Models as Superpositions of Cultural Perspectives
Flowers Team, INRIA（法国国家信息与自动化研究所 Flowers 团队）；Graduate School of Information Science and Technology, The University of Tokyo（东京大学信息科学与技术研究生院）；Ubisoft La Forge（育碧 La Forge）；MIT（麻省理工学院）；INSERM UMR1093-CAPS, Université Bourgogne（法国国家健康与医学研究院 UMR1093-CAPS，勃艮第大学）；Robot Cognition Laboratory, Institute Marey（马雷研究所机器人认知实验室）
CuMA: Aligning LLMs with Sparse Cultural Values via Demographic-Aware Mixture of Adapters
Southeast University（东南大学）；ByteDance Inc.（字节跳动公司）；Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China（新一代人工智能技术及其交叉应用重点实验室（东南大学），中华人民共和国教育部，中国）
Is AI Catching Up to Human Expression? Exploring Emotion, Personality, Authorship, and Linguistic Style in English and Arabic with Six Large Language Models
College of Computer and Information Sciences, King Saud University（计算机与信息科学学院，沙特阿拉伯国王沙德大学）
University of Zagreb（萨格勒布大学）；Faculty of Electrical Engineering and Computing, University of Zagreb（萨格勒布大学电气工程与计算学院）
Personality and demographics are important variables in social sciences, while in NLP they can aid in interpretability and removal of societal biases. However, datasets with both personality and demographic labels are scarce. To address this, we present PANDORA, the first large-scale dataset of Reddit comments labeled with three personality models (including the well-established Big 5 model) and demographics (age, gender, and location) for more than 10k users. We showcase the usefulness of this dataset on three experiments, where we leverage the more readily available data from other personali…
Culturally uneven urban perception in large language models
Centre for Advanced Spatial Analysis (CASA), UCL, London, UK（高级空间分析中心（CASA），伦敦大学学院，英国）；School of Architecture, Tsinghua University, Beijing, China（清华大学建筑学院，北京，中国）；Department of Computer Science, UT Austin, Austin, TX, USA（得克萨斯大学奥斯汀分校计算机科学系，奥斯汀，德克萨斯，美国）
Is ChatGPT a Good Personality Recognizer? A Preliminary Study
Institute of AI Education, East China Normal University（华东师范大学人工智能教育研究院）；School of Computer Science and Technology, East China Normal University（华东师范大学计算机科学与技术学院）；School of Psychology and Cognitive Science, East China Normal University（华东师范大学心理与认知科学学院）；Shanghai Changning Mental Health Center（上海市长宁区精神卫生中心）
Cross-cultural value alignment frameworks for responsible AI governance: Evidence from China-West comparative analysis
Wuhan University of Science and Technology（武汉理工大学）；The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州））；University of Copenhagen（哥本哈根大学）；WUST-Madrid Complutense Institute（武汉理工大学-马德里康普顿斯研究所）
Tilburg University（蒂尔堡大学）；University College London（伦敦大学学院）
Language models such as GPT-3 have caused a furore in the research community. Some studies found that GPT-3 has some creative abilities and makes mistakes that are on par with human behaviour. This paper answers a related question: Who is GPT-3? We administered two validated measurement tools to GPT-3 to assess its personality, the values it holds and its self-reported demographics. Our results show that GPT-3 scores similarly to human samples in terms of personality and - when provided with a model response memory - in terms of the values it holds. We provide the first evidence of psychologic…
PsychAdapter: Adapting LLM Transformers to Reflect Traits, Personality and Mental Health
Stony Brook University（石溪大学）；New York University（纽约大学）；University of Melbourne（墨尔本大学）；University of Texas at Dallas（德克萨斯大学达拉斯分校）；University of Pennsylvania（宾夕法尼亚大学）；Stanford University（斯坦福大学）
Automatic Item Generation for Personality Situational Judgment Tests with Large Language Models
Beijing Normal University（北京师范大学）；Central China Normal University（华中师范大学）；Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education（教育部青少年网络心理与行为重点实验室）；Beijing Key Laboratory of Applied Experimental Psychology（北京市应用实验心理学重点实验室）；Research Center for Capacity Building in Educational Assessment and Evaluation (Beijing Higher Education Innovation Center for Philosophy and Social Sciences)（教育评价与评估能力建设研究中心（北京高等教育哲学社会科学创新中心））
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）
The Cultural Psychology of Large Language Models: Is ChatGPT a Holistic or Analytic Thinker?
New York University（纽约大学）；University of Chicago（芝加哥大学）；Massachusetts Institute of Technology（麻省理工学院）；Johns Hopkins University（约翰斯·霍普金斯大学）；University of California Los Angeles（加州大学洛杉矶分校）
Linguistic markers of personality traits have been studied extensively, but few cross-cultural studies exist. In this paper, we evaluate how native speakers of American English and Arabic perceive personality traits and naturalness of English utterances that vary along the dimensions of verbosity, hedging, lexical and syntactic alignment, and formality. The utterances are the turns within dialogue fragments that are presented as text transcripts to the workers of Amazon's Mechanical Turk. The results of the study suggest that all four dimensions can be used as linguistic markers of all persona…
WorldValuesBench: A Large-Scale Benchmark Dataset for Multi-Cultural Value Awareness of Language Models
University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校）；Allen Institute for Artificial Intelligence（艾伦人工智能研究所）；University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）
University of Pennsylvania（宾夕法尼亚大学）；University of Maryland:ARLIS（马里兰大学：ARLIS）；National Institute on Drug Abuse（国家药物滥用研究所）；Friedrich-Schiller-Universität Jena（耶拿弗里德里希·席勒大学）；Stanford University（斯坦福大学）；New York University（纽约大学）
Empathy is a cognitive and emotional reaction to an observed situation of others. Empathy has recently attracted interest because it has numerous applications in psychology and AI, but it is unclear how different forms of empathy (e.g., self-report vs counterpart other-report, concern vs. distress) interact with other affective phenomena or demographics like gender and age. To better understand this, we created the {\it Empathic Conversations} dataset of annotated negative, empathy-eliciting dialogues in which pairs of participants converse about news articles. People differ in their perceptio…
People's personality and motivations are manifest in their everyday language usage. With the emergence of social media, ample examples of such usage are procurable. In this paper, we aim to analyze the vocabulary used by close to 200,000 Blogger users in the U.S. with the purpose of geographically portraying various demographic, linguistic, and psychological dimensions at the state level. We give a description of a web-based tool for viewing maps that depict various characteristics of the social media users as derived from this large blog dataset of over two billion words.
