Human Behavior Modeling

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27 papers6 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Model Capacity Frontier: A Development Framework for LLM-Supported Social Simulation
Oct 16, 2026Patrick Zhao, Yuxuan Li, Hirokazu ShiradoLarge Language Model-Based Social Simulation Agent-Based Modeling
Simon Fraser University Burnaby, Canada · Carnegie Mellon University Pittsburgh, USA
Preservation and loss of algorithmic structure in experimental diffusion of joint-action norms
Oct 16, 2026Dhara Yu, Bill D. ThompsonCultural Evolution Social Reasoning
Department of Psychology, University of California, Berkeley
Cross-Centaur: Modeling Individual Decision-Making Across Psychological Tasks with Language Models
Oct 16, 2026Hikaru Asano, Hidezo Suganuma, Ryutaro Mori +1Human Behavior Modeling Human Behavior Prediction
The University of Tokyo · RIKEN Center for Brain Science
Large language model-generated patterns for epidemiological modeling: a multi-benchmark evaluation framework
Oct 11, 2026Sophia Mao, Keshav Gandhi, Alexander GutfraindHuman Behavior Modeling LLM Evaluation
Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, 1603 W. Taylor St., Chicago, IL, USA · Program for Experimental and Theoretical Modeling, Division of Hepatology, Department of Medicine, Loyola University Chicago, Maywood, IL 60153, USA
A small cognitive core explains human behavior at scale
Oct 9, 2026Marcel Binz, Eric SchulzCognitive Modeling Human Behavior Modeling
Institute for Human-Centered AI, Helmholtz Munich, Neuherberg, Germany · Max Planck Institute for Biological Cybernetics, Tübingen, Germany
MotiveMob: Motivation as Semantic Action for Closed-Loop Human Mobility Generation
Oct 8, 2026Mengkun Gao, Zengqing Wu, Renhe Jiang +6Human Behavior Modeling Trajectory Generation
The University of Osaka · The University of Tokyo · The Hong Kong University of Science and Technology +1
Sparks of In Silico Cognitive Science: Theories from Simulated Data Can Generalize to Humans
Sep 7, 2026Akshay K. Jagadish, Younes Strittmatter, Nori Jacoby +4Computational Cognitive Modeling Human Behavior Simulation
Princeton University · Cornell University · Helmholtz Munich
More accurate behavioral predictions with hybrid Bayesian-connectionist models
Aug 23, 2026Brenden M. Lake, Akshay K. Jagadish, Guangyuan JiangComputational Cognitive Modeling Human Behavior Modeling
Departments of Computer Science and Psychology, Princeton University · Princeton AI Lab, Princeton University · Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology
Modeling Human Behavior with Type Vectors Using AI
Aug 18, 2026Matthew O. Jackson, Benjamin S. Manning, Yutong Xie +2Human Behavior Simulation Human Behavior Prediction
Stanford University, Santa Fe Institute, Monash University · Moblab · MIT, MIT Initiative on the Digital Economy +2
Small Foundation Models of Human Cognition and Behaviour
Aug 5, 2026Nick Oh, Fernand GobetComputational Cognitive Modeling Human Behavior Modeling
socius labs · London School of Economics and Political Science
Mental World Modeling
Jul 29, 2026Hao Fei, Yiran ZhaoWorld Model Learning Theory of Mind
University of Oxford · National University of Singapore
BehaviorBench: Benchmarking Foundation Models for Behavioral Science Tasks
Jun 23, 2026Jin Huang, Yutong Xie, Wanli Song +5Benchmark Design Human Behavior Simulation
University of Michigan · MobLab · Stanford University +1
Using Cognitive Models to Improve Language Model Simulation of Human Persuasion Games
Jun 16, 2026Zirui Cheng, Zeyu Shen, Thomas L. Griffiths +1Persuasion in Language Models Cognitive Modeling
1Princeton University
BehaviorBench: Modeling Real-World User Decisions from Behavioral Traces
Jun 1, 2026Liangwei Yang, Jielin Qiu, Zixiang Chen +9Forecasting Benchmarks User Modeling
Salesforce AI Research
Early Prediction of Future Behavioral Strategy from Process Traces
May 28, 2026Robert Kasumba, Dennis Barbour, Chien-Ju HoLatent Variable Models Human Behavior Modeling
Division of Computational and Data Sciences Washington University in Saint Louis Saint Louis, MO 63130 · Department of Biomedical Engineering Washington University in Saint Louis Saint Louis, MO 63130 · Department of Computer Science Washington University in Saint Louis Saint Louis, MO 63130
BEHAVE: Real-Time Modeling of Human Systems as Observable Complex Dynamical Systems and Operational Objects for Physical AI
May 12, 2026Helene MalyutinaDynamical Systems Pedestrian Behavior Modeling
Independent Researcher, Collective Dynamics Lab
How Well Do Large Language Models Capture Human Personality?
May 12, 2026Aanisha Bhattacharyya, Yaman Kumar Singla, Rajiv Ratn Shah +2Persona-Conditioned Generation Representation Collapse
Adobe Media and Data Science Research (MDSR) · IIIT-Delhi · SUNY at Buffalo
Reason to Play: Behavioral and Brain Alignment Between Frontier LRMs and Human Game Learners
May 8, 2026Botos Csaba, Sreejan Kumar, Austin Tudor David Andrews +6Game-Playing Agents Human Behavior Simulation
University of Oxford · Columbia University · New York University +2
Post-training makes large language models less human-like
May 8, 2026Marcel Binz, Elif Akata, Abdullah Almaatouq +76LLM Evaluation LLM Alignment
Think-Aloud Reshapes Automated Cognitive Model Discovery Beyond Behavior
May 6, 2026Hanbo Xie, Akshay K. Jagadish, Lan Pan +1Computational Cognitive Modeling Human Behavior Modeling
School of Psychology, Georgia Institute of Technology · Princeton AI Lab, Princeton University · Center of Excellence for Computational Cognition, Georgia Institute of Techonology
Hierarchical Multi-Persona Induction from User Behavioral Logs: Learning Evidence-Grounded and Truthful Personas
Apr 28, 2026Nayoung Choi, Haeyu Jeong, Changbong Kim +2Personality Modeling in Language Models User Modeling
Department of Computer Science, Emory University, Atlanta, GA, USA · Naver Corporation, South Korea
LLMs Reading the Rhythms of Daily Life: Aligned Understanding for Behavior Prediction and Generation
Apr 26, 2026Fanjin Meng, Jingtao Ding, Nian Li +2LLM Alignment Human Behavior Modeling
Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China
Multi-Cycle Spatio-Temporal Adaptation in Human-Robot Teaming
Apr 21, 2026Alex Cuellar, Michael Hagenow, Julie ShahHuman Behavior Modeling Human-Robot Collaboration
MIT CSAIL · UW Madison Department of Computer Science
Improving Human Performance with Value-Aware Interventions: A Case Study in Chess
Apr 15, 2026Saumik Narayanan, Raja Panjwani, Siddhartha Sen +1Human Behavior Modeling AI-Assisted Decision Making
Washington University in St. Louis · Microsoft Research · Georgetown University
Context-Value-Action Architecture for Value-Driven Large Language Model Agents
Apr 7, 2026TianZe Zhang, Sirui Sun, Yuhang Xie +3Human Behavior Modeling LLM Agents
State Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University · Yuanpei College, Peking University · School of Psychological and Cognitive Sciences, Peking University +2
Alignment Makes Language Models Normative, Not Descriptive
Mar 17, 2026Eilam Shapira, Moshe Tennenholtz, Roi ReichartLLM Alignment Preference Alignment
Technion – Israel Institute of Technology
HugAgent: A Human Simulation Benchmark for Individual-Level Reasoning
Oct 16, 2025Chance Jiajie Li, Zhenze Mo, Yuhan Tang +11Cognitive Modeling Human Behavior Simulation
1MIT Media Lab · 8Northeastern University · 5MIT CEE +7

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Model Capacity Frontier: A Development Framework for LLM-Supported Social Simulation

Patrick Zhao, Yuxuan Li, Hirokazu Shirado

Simon Fraser University Burnaby, Canada · Carnegie Mellon University Pittsburgh, USA

Large Language Model-Based Social Simulation Agent-Based Modeling Human Behavior Modeling

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Large language model (LLM) agents are increasingly incorporated into agent-based models (ABMs) on the premise that richer, context-sensitive human behavior can improve empirical fidelity. However, LLM-supported ABMs introduce an open-ended design space in which subtle modeling and configuration choices, such as prompt design and environment coupling, can substantially alter outcomes. Developing LLM-supported ABMs to simulate human collective behavior therefore requires navigating configuration sensitivity while identifying the limitations of the current model architecture. In this paper, we introduce the Model Capacity Frontier (MCF), a framework that characterizes the empirical performance attainable by a specified architecture across its admissible configurations. In multi-objective settings, this capacity is represented by an estimated Pareto frontier obtained through systematic configuration exploration. We demonstrate MCF in crowd simulation of university commencement events with approximately 12,000 agents, using empirical movement data on temporal occupancy, spatial distribution, and flow direction. We first characterize the capacity of a conventional crowd model and then evaluate successive LLM-supported architectural extensions. In the process, MCF reveals which dimensions of attainable performance expand and which remain limited, providing empirical targets for refinement and re-evaluation. Initial LLM integration improves flow direction but degrades temporal occupancy and spatial distribution; subsequent architectural refinement of the LLM layer improves temporal occupancy and recovers spatial performance, while retaining much of the earlier gain in flow direction. Our case study shows how MCF guides the systematic architectural development of LLM-supported ABMs in configuration-sensitive, open-ended design spaces.