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Be.FM: Open Foundation Models for Human Behavior

https://doi.org/10.2139/ssrn.5274559
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Tutorial: Applying Machine Learning in Behavioral Research
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Applications of machine learning to behavioral sciences: focus on categorical data
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Click-through rate prediction in online advertising: A literature review
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An experimental test of the crowding out hypothesis
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Synthetic Replacements for Human Survey Data? The Perils of Large Language Models
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“Economic man” in cross-cultural perspective: Behavioral experiments in 15 small-scale societies
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Highly accurate protein structure prediction with AlphaFold
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ChatGPT outperforms crowd workers for text-annotation tasks
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Systematic testing of three Language Models reveals low language accuracy, absence of response stability, and a yes-response bias
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A Turing test of whether AI chatbots are behaviorally similar to humans
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Can Generative AI improve social science?
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The emergence of economic rationality of GPT
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AI emerges as the frontier in behavioral science
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Can large language models help predict results from a complex behavioural science study?
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Machine Learning Techniques for Sentiment Analysis of COVID-19-Related Twitter Data
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Evidence from an Experiment on Charity to Welfare Recipients: Reciprocity, Altruism and the Empathic Responsiveness Hypothesis
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AI and the transformation of social science research
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Synerise Monad: A Foundation Model for Behavioral Event Data
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Generative Agents: Interactive Simulacra of Human Behavior
inferredcites →https://doi.org/10.1145/3670865.3673513openalex-snapshot
Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?
inferredcites →https://doi.org/10.1145/3717867.3717903openalex-snapshot
Accuracy and Political Bias of News Source Credibility Ratings by Large Language Models
inferredcites →https://doi.org/10.1162/jeea.2010.8.1.120openalex-snapshot
What Do We Expect from Our Friends?
inferredcites →https://doi.org/10.1177/0002764219859639openalex-snapshot
Advances in Machine Learning for the Behavioral Sciences
inferredcites →https://doi.org/10.1201/9781003472094openalex-snapshot
Applied Survey Data Analysis
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Centaur: a foundation model of human cognition
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The Generalizability Crisis
inferredcites →https://doi.org/10.48550/arxiv.2011.03395openalex-snapshot
Underspecification Presents Challenges for Credibility in Modern Machine Learning
inferredcites →https://doi.org/10.48550/arxiv.2106.09685openalex-snapshot
LoRA Fine-Tuning of a 3B Code LLM for Algorithmic Efficiency
inferredcites →https://doi.org/10.48550/arxiv.2208.10264openalex-snapshot
Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies
inferredcites →https://doi.org/10.48550/arxiv.2303.12712openalex-snapshot
Sparks of Artificial General Intelligence: Early experiments with GPT-4
inferredcites →https://doi.org/10.48550/arxiv.2303.17548openalex-snapshot
Whose Opinions Do Language Models Reflect?
inferredcites →https://doi.org/10.48550/arxiv.2405.06058openalex-snapshot
Large Language Models Show Human-like Social Desirability Biases in Survey Responses
inferredcites →https://doi.org/10.48550/arxiv.2411.10109openalex-snapshot
LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals
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How Different AI Chatbots Behave? Benchmarking Large Language Models in Behavioral Economics Games
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