The academic reference hub.

01 MatrAIx: Simulating the World with 8.3 Billion Persona Agents A population-scale simulated-user evaluation infrastructure that tests AI systems and digital products with 8.3 billion persona records and 1,010 reusable tasks. ↗ 02 Beyond Demographics: Aligning Role-playing LLM-based Agents Using Human Belief Networks Alignment of LLM agents with human behavior: the impact of demographic information and belief networks on opinion imitation accuracy. ↗ 03 Do LLM Agents Exhibit Social Behavior? LLM behavior in social interactions: the role of group identity, reciprocity mechanisms, and chain-of-thought processes in predicting social behavior. ↗ 04 Enhancing LLM Decision-Making with Factor Profiles and Analogical Reasoning (DEFINE) Rational decision-making by LLMs in financial scenarios under uncertainty: improving decision accuracy and transparency through factor profiles and historical analogy. ↗ 05 Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus? The capacity of LLMs to imitate human agents in behavioral economics experiments: model diversity, endowment effects, and experimental reproducibility. ↗ 06 Large Language Models as Subpopulation Representative Models: A Review Using LLMs as subpopulation representative models (SRMs): potential for measuring public opinion and a risk–benefit assessment. ↗ 07 Large Language Models Empowered Agent-Based Modeling and Simulation: A Survey and Perspectives The role of LLMs in agent-based modeling and simulation (ABMS): transforming simulation paradigms through human-like intelligence and behavior. ↗ 08 LLM-Based Doppelgänger Models: Leveraging Synthetic Data for Human-Like Responses Learning and imitating individual opinions with an LLM-based Doppelgänger model: accuracy, heterogeneity, and single-device feasibility. ↗ 09 LLMs and Generative Agent-Based Models for Complex Systems The capacity of LLM agents to imitate human-like behavior across multiple social systems and the modeling of complex social dynamics using Generative Agent-Based Models (GABMs). ↗ 10 LLMs’ Ways of Seeing User Personas LLMs’ ability to perceive and interpret user personas: the impact of cultural context and the capacity to reconstruct demographic profiles. ↗ 11 Reduce Disparity Between LLMs and Humans: Optimal LLM Sample Calibration Calibration of LLMs across demographic groups: human alignment and transferability using Human Mimicry Calibration (HMC). ↗ 12 Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization Persona usage in LLMs: the distinction between role-playing and personalization, application domains, and personality assessment methods. ↗ 13 Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies The capacity of LLMs to simulate human behavior across classical experiments and diverse demographic profiles: model scale, demographic variation, and hyper-accuracy effects. ↗ 14 Analyzing Brand Perception in LLMs Evaluating how biased and how consistent LLMs are toward brands. ↗ 15 Can LLMs Capture Human Preferences? The ability of LLMs to imitate human preferences and the effects of language and chain-of-thought methods. ↗ 16 Comparing Traditional and LLM-based Search for Consumer Choice: A Randomized Experiment Examining the effects of LLM-based search systems on efficiency, accuracy, user perception, and error handling compared to traditional search, and the role of confidence cues. ↗