A semantic embedding space based on large language models for modelling human beliefs

2025/06/04 by Byunghwee Lee, Rachith Aiyappa, Yong-Yeol Ahn +3 · 1 voice · 2 citations
Neuroscience · #Cognitive Science and Education Research

paper · doi:10.1038/s41562-025-02228-z

openalex created_date 2024/09/11 · crossref issued 2025/06/04 · crossref published 2025/06/04 · crossref published-online 2025/06/04 · openalex publication_date 2025/06/04 · crossref created 2025/06/04 · crossref deposited 2025/09/24 · crossref indexed 2026/02/20 · openalex updated_date 2026/07/28

Citations

• The echo chamber effect on social media
• Statistical physics of social dynamics
• Mixing beliefs among interacting agents
• Social influence and opinions
• Llama 2: Open Foundation and Fine-Tuned Chat Models
• Bias and Fairness in Large Language Models: A Survey
• Matrix Factorization Techniques for Recommender Systems
• Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System

Cited by

• The Roots of International Perceptions: Simulating US Attitude Changes Towards China with LLM Agents
• A semantic atlas of journals: Structure, position, and dispersion

Discussions

• 📢 Exciting news! Our two-year project at Indiana University has just been published in Nature Human Behaviour!
🔗 doi.org/10.1038/s415... In this study, we used large language models and a massive on [bsky, 1 points, 1 comments]