mlsanityData to 14 Oct 2026

Be.FM: Open Foundation Models for Human Behavior

arXiv 2505.23058 ↗First posted 29 May 2025cs.AI cs.CE cs.CLcited by 9

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Abstract (arXiv)

Despite their success in numerous fields, the potential of foundation models for modeling and understanding human behavior remains largely unexplored. We introduce Be.FM, one of the first open foundation models designed for human behavior modeling. Built upon open-source large language models and fine-tuned on a diverse range of behavioral data, Be.FM can be used to understand and predict human decision-making. We construct a comprehensive set of benchmark tasks for testing the capabilities of behavioral foundation models. Our results demonstrate that Be.FM can predict behaviors, infer characteristics of individuals and populations, generate insights about contexts, and apply behavioral science knowledge.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 19 of its 51 references that are in the map. First posted on arXiv 29 May 2025.

Builds on

19 of 51 references.

References · 19

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
  3. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,592
  4. 2024LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Modelscited by 1,464
  5. 2023ChatGPT Outperforms Crowd-Workers for Text-Annotation Taskscited by 870
  6. 2023Whose Opinions Do Language Models Reflect?cited by 773
  7. 2022Out of One, Many: Using Language Models to Simulate Human Samplescited by 752
  8. 2022Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studiescited by 515
  9. 2020Underspecification Presents Challenges for Credibility in Modern Machine Learningcited by 496
  10. 2024LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individualscited by 249
  11. 2025Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Modelscited by 56
  12. 2023Strategic Behavior of Large Language Models: Game Structure vs. Contextual Framingcited by 51
7 more
  1. 2024Centaur: a foundation model of human cognitioncited by 36
  2. 2022Click-Through Rate Prediction in Online Advertising: A Literature Reviewcited by 31
  3. 2024Large Language Models Show Human-like Social Desirability Biases in Survey Responsescited by 28
  4. 2025Fast Adaptation with Behavioral Foundation Modelscited by 21
  5. 2024MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflowscited by 19
  6. 2024How Different AI Chatbots Behave? Benchmarking Large Language Models in Behavioral Economics Gamescited by 6
  7. 2019Advances in Machine Learning for the Behavioral Sciencescited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 6.

9 papers.

  1. 2025Finetuning LLMs for Human Behavior Prediction in Social Science Experimentscited by 39
  2. 2025Population-Aligned Persona Generation for LLM-based Social Simulationcited by 21
  3. 2026HumanLLM: Towards Personalized Understanding and Simulation of Human Naturecited by 8
  4. 2025Graph-Based Alternatives to LLMs for Human Simulationcited by 1
  5. 2026GroupGPT: A Token-efficient and Privacy-preserving Agentic Framework for Multi-User Chat Assistantcited by 1
  6. 2026BehaviorBench: Benchmarking Foundation Models for Behavioral Science Taskscited by 1
  7. 2026Small Foundation Models of Human Cognition and Behaviourcited by 1
  8. 2026HouseholdBench: Evaluating Large Language Models as Predictors of Household Economic Behaviorcited by 0
  9. 2026Socio-Foundation: A Model for Generalizable Individual Behavior Simulation via Hierarchical Capability Distillationcited by 0