As Large Language Models are deployed within Artificial Intelligence systems, that are increasingly integrated with human society, it becomes more important than ever to study their internal structures. Higher level abilities of LLMs such as GPT-3.5 emerge in large part due to informative language representations they induce from raw text data during pre-training on trillions of words. These embeddings exist in vector spaces of several thousand dimensions, and their processing involves mapping between multiple vector spaces, with total number of parameters on the order of trillions. Furthermore, these language representations are induced by gradient optimization, resulting in a black box system that is hard to interpret. In this paper, we take a look at the topological structure of neuronal activity in the "brain" of Chat-GPT's foundation language model, and analyze it with respect to a metric representing the notion of fairness. We develop a novel approach to visualize GPT's moral dimensions. We first compute a fairness metric, inspired by social psychology literature, to identify factors that typically influence fairness assessments in humans, such as legitimacy, need, and responsibility. Subsequently, we summarize the manifold's shape using a lower-dimensional simplicial complex, whose topology is derived from this metric. We color it with a heat map associated with this fairness metric, producing human-readable visualizations of the high-dimensional sentence manifold. Our results show that sentence embeddings based on GPT-3.5 can be decomposed into two submanifolds corresponding to fair and unfair moral judgments. This indicates that GPT-based language models develop a moral dimension within their representation spaces and induce an understanding of fairness during their training process.
Human Values in a Single Sentence: Moral Presence, Hierarchies, and Transformer Ensembles on the Schwartz Continuum
PRHLT Research Center, Universitat Politècnica de València（PRHLT研究中心，巴塞罗那理工大学）；School of Science, Engineering and Design, Universidad Europea de Valencia（科学、工程与设计学院，欧洲大学瓦伦西亚分校）；Valencian Graduate School（瓦伦西亚研究生学院）；Research Network of Artificial Intelligence (ValgrAI)（人工智能研究网络（ValgrAI））
Whose Morality Do They Speak? Unraveling Cultural Bias in Multilingual Language Models
Research Center Trustworthy Data Science and Security of the University Alliance Ruhr（鲁尔大学联盟可信数据科学与安全研究中心）；Faculty of Informatics, Technical University Dortmund（多特蒙德工业大学信息学院）
Moral Susceptibility and Robustness under Persona Role-Play in Large Language Models
TELUS Digital Research Hub（TELUS数字研究中心）；Center for Artificial Intelligence and Machine Learning（人工智能与机器学习中心）；Institute of Mathematics, Statistics and Computer Science（数学、统计与计算机科学研究所）；University of São Paulo（圣保罗大学）
Are Large Language Models Moral Hypocrites? A Study Based on Moral Foundations
Pontifical Catholic University of Rio de Janeiro（里约热内卢天主教大学）；FGV Direito Rio（FGV里约法学院）；Insper Institute of Education and Research（Insper教育与研究学院）；Federal University of Rio de Janeiro（里约热内卢联邦大学）；State University of Rio de Janeiro（里约热内卢州立大学）
UM_FHS at the CLEF 2025 SimpleText Track: Comparing No-Context and Fine-Tune Approaches for GPT-4.1 Models in Sentence and Document-Level Text Simplification
University of Maribor, Faculty of Health Science（马里博大学健康科学学院）；University of Ljubljana, Faculty of Medicine（卢布尔雅那大学医学院）；University of Edinburgh, Usher Institute（爱丁堡大学usher研究所）
Exploring the psychology of LLMs' Moral and Legal Reasoning
INSPER Institute of Education and Research（INSPER 教育与研究学院）；FGV Direito Rio（FGV 里约法学院）；PUC-Rio（里约热内卢天主教大学）；Center for Humans and Machines, Max Planck Institute for Human Development（马克斯·普朗克人类发展研究所人类与机器中心）；Ruhr-University Bochum（波鸿鲁尔大学）；Federal University of Rio de Janeiro（里约热内卢联邦大学）；State University of Rio de Janeiro（里约热内卢州立大学）
The Moral Consistency Pipeline: Continuous Ethical Evaluation for Large Language Models
SWAT Laboratory, Polytechnique Montréal（蒙特利尔大学SWAT实验室）；Concordia Institute for Information Systems Engineering, Concordia University（Concordia大学信息系统工程研究所）
Large-scale moral machine experiment on large language models
Department of Bioscience and Bioinformatics, Kyushu Institute of Technology（九州工科大学生物科学与生物信息学系）；Faculty of Engineering and Technology, Multimedia University（多媒体大学工程与技术学院）；Data Science and AI Research Center, Kyushu Institute of Technology（九州工科大学数据科学与人工智能研究中心）
Social Catalysts, Not Moral Agents: The Illusion of Alignment in LLM Societies
Institute of Neuroscience, Chinese Academy of Sciences（中国科学院神经科学研究所）；School of Philosophy, Anhui University（安徽大学哲学学院）；Department of Psychology and Behavioral Sciences, Zhejiang University（浙江大学心理学与行为科学系）；Mental Health Education Center, North China Electric Power University（华北电力大学心理健康教育中心）
Beyond Value Elicitation: Towards Moral Profiles in Early Requirements Engineering via Role-Playing Games and Anthropologist LLMs
Computer Science Area, Gran Sasso Science Institute（格兰萨索科学研究所计算机科学部门）；Department of Computer Science, University of Pisa（比萨大学计算机科学系）；Department of Humanities, University of L’Aquila（拉奎拉大学人文学系）
Large Pre-trained Language Models Contain Human-like Biases of What is Right and Wrong to Do
Technical University of Darmstadt（达姆施塔特工业大学）；Leibniz Institute for Research and Information in Education（莱布尼茨教育研究与信息研究所）；Hessian Center for Artificial Intelligence (hessian.ai)（黑森州人工智能中心）
More Context, Larger Models, or Moral Knowledge? A Systematic Study of Schwartz Value Detection in Political Texts
PRHLT Research Center, Universitat Politècnica de València, Spain（巴塞罗那理工大学研究中心，西班牙 Valencia理工大学）；School of Science, Engineering and Design, Universidad Europea de Valencia, Spain（Valencia欧洲大学科学、工程与设计学院，西班牙）；Valencian Graduate School and Research Network of Artificial Intelligence (ValgrAI)（瓦伦西亚人工智能研究生学院与研究网络（ValgrAI））
TELUS Digital Research Hub（TELUS数字研究中心）；Center for Artificial Intelligence and Machine Learning（人工智能与机器学习中心）；Institute of Mathematics, Statistics and Computer Science（数学、统计与计算机科学研究所）；University of São Paulo（圣保罗大学）
McGill University（麦吉尔大学）；Mila - Quebec AI Institute（米拉-魁北克人工智能研究所）；University College London（伦敦大学学院）；National Research Council Canada（加拿大国家研究委员会）；Facebook（脸书）
Comparing Human and Language Models Sentence Processing Difficulties on Complex Structures
Blavatnik School of Computer Science, Tel Aviv University, Israel（巴尔-艾塔夫大学计算机科学学院）；Department of Linguistics, Tel Aviv University, Israel（巴尔-艾塔夫大学语言学系）；Sagol School of Neuroscience, Tel Aviv University, Israel（巴尔-艾塔夫大学神经科学学院）
