ArticleBehavior research methods2024
A tutorial on open-source large language models for behavioral science.
Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Deep Semantics Analysis for Scale Development: Replicating Psychometrics Validation Process with Large Language Models.Behavioral sciences (Basel, Switzerland) · 2026Article
- Adding LLMs to the psycholinguistic norming toolbox: A practical guide to getting the most out of human ratings.Behavior research methods · 2026Article
- Large language models accurately identify decision reasons in verbal reports.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- A validity-guided workflow for robust large language model research in psychology.Behavior research methods · 2026Article
- Generative psychometrics via AI-GENIE: Automatic item generation and validation with network-integrated evaluation.Behavior research methods · 2026Article
- Escaping the Jingle-Jangle Jungle: Increasing Conceptual Clarity in Psychology Using Large Language Models.Current directions in psychological science · 2026Article
- Snake Oil or Panacea? How to Misuse AI in Scientific Inquiries of the Human Mind.Behavioral sciences (Basel, Switzerland) · 2026Review
- Human Expertise and Large Language Model Embeddings in the Content Validity Assessment of Personality Tests.Educational and psychological measurement · 2026Article
- Large Language Models as Distributional Baselines for Language Tasks.Open mind : discoveries in cognitive science · 2026Article
- A review for navigating the trade-offs: evaluating open-source and proprietary large language models for clinical and biomedical information extraction.Frontiers in digital health · 2026Review
- Mapping relational mechanism clusters inFrontiers in psychology · 2026Article
- Updating the German Psycholinguistic Word Toolbox with AI-Generated Estimates of Concreteness, Valence, Arousal, Age of Acquisition, and Familiarity.Journal of cognition · 2026Article
- Evaluating Web Retrieval-Assisted Large Language Models With and Without Whitelisting for Evidence-Based Neurology: Comparative Study.Journal of medical Internet research · 2025Article
- Crowdsourced and AI-generated age-of-acquisition (AoA) norms for vocabulary in print: Extending the Kuperman et al. (2012) norms.Behavior research methods · 2025Article
- Simulating lexical decision times with large language models to supplement megastudies and crowdsourcing.Behavior research methods · 2025Article
- Semantic embeddings reveal and address taxonomic incommensurability in psychological measurement.Nature human behaviour · 2025Article
- Predicting MBTI personality of YouTube users.Scientific reports · 2025Article
- AI can outperform humans in predicting correlations between personality items.Communications psychology · 2025Article
- Using large language models to facilitate academic work in the psychological sciences.Current psychology (New Brunswick, N.J.) · 2025Article
- Mapping Mental Representations With Free Associations: A Tutorial Using the R Package associatoR.Journal of cognition · 2025Article
Corrections and comments
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4 authors.
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Abstract
Large language models (LLMs) have the potential to revolutionize behavioral science by accelerating and improving the research cycle, from conceptualization to data analysis. Unlike closed-source solutions, open-source frameworks for LLMs can enable transparency, reproducibility, and adherence to data protection standards, which gives them a crucial advantage for use in behavioral science. To help researchers harness the promise of LLMs, this tutorial offers a primer on the open-source Hugging Face ecosystem and demonstrates several applications that advance conceptual and empirical work in behavioral science, including feature extraction, fine-tuning of models for prediction, and generation of behavioral responses. Executable code is made available at github.com/Zak-Hussain/LLM4BeSci.git . Finally, the tutorial discusses challenges faced by research with (open-source) LLMs related to interpretability and safety and offers a perspective on future research at the intersection of language modeling and behavioral science.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.