Semantic analysis of test items through large language model embeddings predicts a-priori factorial structure of personality tests
In this article, we explore the use of Large Language Models (LLMs) for predicting factor loadings in personality tests through the semantic analysis of test items. By leveraging text embeddings generated from LLMs, we evaluate the semantic similarity of test items and their alignment with hypothesi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
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| Series: | Current Research in Behavioral Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666518225000014 |
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