# SocioVerse: A World Model for Social Simulation Powered by LLM Agents and A Pool of 10 Million Real-World Users

arXiv: https://arxiv.org/abs/2504.10157 · HTML: https://mlsanity.com/paper/2504.10157/

## Key facts

- Cited by 55 papers in the map (data through 14 Oct 2026).
- Placed in World models for language agents, one of 11 directions in World models.
- Builds on 33 of its 62 references that are in the map.
- First posted on arXiv 14 Apr 2025.

## Placed in

- World models / [World models for language agents](https://mlsanity.com/wm/world-models-for-language-agents/)
- LLM agents and tool use / [Social simulation and multi-agent debate](https://mlsanity.com/agents/social-simulation-and-multi-agent-debate/)

## Builds on (most cited first, 30 of 33)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [The Llama 3 Herd of Models](https://mlsanity.com/paper/2407.21783/) (2024)
- [DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning](https://mlsanity.com/paper/2501.12948/) (2025)
- [Efficient Memory Management for Large Language Model Serving with PagedAttention](https://mlsanity.com/paper/2309.06180/) (2023)
- [Qwen2.5 Technical Report](https://mlsanity.com/paper/2412.15115/) (2024)
- [GPT-4o System Card](https://mlsanity.com/paper/2410.21276/) (2024)
- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Longformer: The Long-Document Transformer](https://mlsanity.com/paper/2004.05150/) (2020)
- [Out of One, Many: Using Language Models to Simulate Human Samples](https://mlsanity.com/paper/2209.06899/) (2022)
- [Character-LLM: A Trainable Agent for Role-Playing](https://mlsanity.com/paper/2310.10158/) (2023)
- [Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives](https://mlsanity.com/paper/2312.11970/) (2023)
- [LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals](https://mlsanity.com/paper/2411.10109/) (2024)
- [S3: Social-network Simulation System with Large Language Model-Empowered Agents](https://mlsanity.com/paper/2307.14984/) (2023)
- [User Behavior Simulation with Large Language Model based Agents](https://mlsanity.com/paper/2306.02552/) (2023)
- [OASIS: Open Agent Social Interaction Simulations with One Million Agents](https://mlsanity.com/paper/2411.11581/) (2024)
- [LLM Social Simulations Are a Promising Research Method](https://mlsanity.com/paper/2504.02234/) (2025)
- [From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents](https://mlsanity.com/paper/2412.03563/) (2024)
- [LLM-Rec: Personalized Recommendation via Prompting Large Language Models](https://mlsanity.com/paper/2307.15780/) (2023)
- [Unveiling the Truth and Facilitating Change: Towards Agent-based Large-scale Social Movement Simulation](https://mlsanity.com/paper/2402.16333/) (2024)
- [From Skepticism to Acceptance: Simulating the Attitude Dynamics Toward Fake News](https://mlsanity.com/paper/2403.09498/) (2024)
- [ElectionSim: Massive Population Election Simulation Powered by Large Language Model Driven Agents](https://mlsanity.com/paper/2410.20746/) (2024)
- [Synergistic Multi-Agent Framework with Trajectory Learning for Knowledge-Intensive Tasks](https://mlsanity.com/paper/2407.09893/) (2024)
- [Simulating Public Administration Crisis: A Novel Generative Agent-Based Simulation System to Lower Technology Barriers in Social Science Research](https://mlsanity.com/paper/2311.06957/) (2023)
- [Identity-Driven Hierarchical Role-Playing Agents](https://mlsanity.com/paper/2407.19412/) (2024)
- [Social physics](https://mlsanity.com/paper/2110.01866/) (2021)
- [SoMeLVLM: A Large Vision Language Model for Social Media Processing](https://mlsanity.com/paper/2402.13022/) (2024)
- [Correcting Sociodemographic Selection Biases for Population Prediction from Social Media](https://mlsanity.com/paper/1911.03855/) (2019)
- [Multi-agent KTO: Reinforcing Strategic Interactions of Large Language Model in Language Game](https://mlsanity.com/paper/2501.14225/) (2025)
- [Computational Agent-based Models in Opinion Dynamics: A Survey on Social Simulations and Empirical Studies](https://mlsanity.com/paper/2306.03446/) (2023)
- [Can Large Language Models Capture Public Opinion about Global Warming? An Empirical Assessment of Algorithmic Fidelity and Bias](https://mlsanity.com/paper/2311.00217/) (2023)

## Built on by (most cited first, 30 of 55)

- [Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models](https://mlsanity.com/paper/2505.04921/) (2025)
- [LLM-based Agentic Reasoning Frameworks: A Survey from Methods to Scenarios](https://mlsanity.com/paper/2508.17692/) (2025)
- [Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond](https://mlsanity.com/paper/2604.22748/) (2026)
- [Simulating Society Requires Simulating Thought](https://mlsanity.com/paper/2506.06958/) (2025)
- [Ready Jurist One: Benchmarking Language Agents for Legal Intelligence in Dynamic Environments](https://mlsanity.com/paper/2507.04037/) (2025)
- [Position: The Real Barrier to LLM Agent Usability is Agentic ROI](https://mlsanity.com/paper/2505.17767/) (2025)
- [LLM-Based Social Simulations Require a Boundary](https://mlsanity.com/paper/2506.19806/) (2025)
- [YuLan-OneSim: Towards the Next Generation of Social Simulator with Large Language Models](https://mlsanity.com/paper/2505.07581/) (2025)
- [LifeSim: Long-Horizon User Life Simulator for Personalized Assistant Evaluation](https://mlsanity.com/paper/2603.12152/) (2026)
- [Modeling Earth-Scale Human-Like Societies with One Billion Agents](https://mlsanity.com/paper/2506.12078/) (2025)
- [EcoLANG: Efficient and Effective Agent Communication Language Induction for Social Simulation](https://mlsanity.com/paper/2505.06904/) (2025)
- [CrowdLLM: Building LLM-Based Digital Populations Augmented with Generative Models](https://mlsanity.com/paper/2512.07890/) (2025)
- [Gender Dynamics and Homophily in a Social Network of LLM Agents](https://mlsanity.com/paper/2602.02606/) (2026)
- [Building Social World Models with Large Language Models](https://mlsanity.com/paper/2606.11482/) (2026)
- [CP-Env: Evaluating Large Language Models on Clinical Pathways in a Controllable Hospital Environment](https://mlsanity.com/paper/2512.10206/) (2025)
- [HyLaT: Efficient Multi-Agent Communication via Hybrid Latent-Text Protocol](https://mlsanity.com/paper/2605.25421/) (2026)
- [AIvilization v0: Toward Large-Scale Artificial Social Simulation with a Unified Agent Architecture and Adaptive Agent Profiles](https://mlsanity.com/paper/2602.10429/) (2026)
- [DynamiX: Large-Scale Dynamic Social Network Simulator](https://mlsanity.com/paper/2507.19929/) (2025)
- [Computational Multi-Agents Society Experiments: Social Modeling Framework Based on Generative Agents](https://mlsanity.com/paper/2508.17366/) (2025)
- [AlignSurvey: A Comprehensive Benchmark for Human Preferences Alignment in Social Surveys](https://mlsanity.com/paper/2511.07871/) (2025)
- [Multilingual Agent-Based World Modeling for Social Science](https://mlsanity.com/paper/2512.07195/) (2025)
- [From Particles to Agents: Hallucination as a Metric for Cognitive Friction in Spatial Simulation](https://mlsanity.com/paper/2601.21977/) (2026)
- [Context-Value-Action Architecture for Value-Driven Large Language Model Agents](https://mlsanity.com/paper/2604.05939/) (2026)
- [IROTE: Human-like Traits Elicitation of Large Language Model via In-Context Self-Reflective Optimization](https://mlsanity.com/paper/2508.08719/) (2025)
- [Assessing Historical Structural Oppression Worldwide via Rule-Guided Prompting of Large Language Models](https://mlsanity.com/paper/2509.15216/) (2025)
- [HAG: Hierarchical Demographic Tree-based Agent Generation for Topic-Adaptive Simulation](https://mlsanity.com/paper/2601.05656/) (2026)
- [Can LLMs Think Like Consumers? Benchmarking Crowd-Level Reaction Reconstruction with ConsumerSimBench](https://mlsanity.com/paper/2605.17079/) (2026)
- [Uncovering Salience-Driven Dynamics in Consumer Confidence with Generative Social Simulation](https://mlsanity.com/paper/2606.30395/) (2026)
- [SocietyBench: Forecasting Counterfactual Social-World Evolution](https://mlsanity.com/paper/2608.04009/) (2026)
- [HelloWorld: Enabling Socially Interactive Characters in Video World Models](https://mlsanity.com/paper/2608.05070/) (2026)

## Abstract (arXiv)

Social simulation is transforming traditional social science research by modeling human behavior through interactions between virtual individuals and their environments. With recent advances in large language models (LLMs), this approach has shown growing potential in capturing individual differences and predicting group behaviors. However, existing methods face alignment challenges related to the environment, target users, interaction mechanisms, and behavioral patterns. To this end, we introduce SocioVerse, an LLM-agent-driven world model for social simulation. Our framework features four powerful alignment components and a user pool of 10 million real individuals. To validate its effectiveness, we conducted large-scale simulation experiments across three distinct domains: politics, news, and economics. Results demonstrate that SocioVerse can reflect large-scale population dynamics while ensuring diversity, credibility, and representativeness through standardized procedures and minimal manual adjustments.