SEMbeddings: how to evaluate model misfit before data collection using large-language models
IntroductionRecent developments suggest that Large Language Models (LLMs) provide a promising approach for approximating empirical correlation matrices of item responses by utilizing item embeddings and their cosine similarities. In this paper, we introduce a novel tool, which we label SEMbeddings.M...
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Main Authors: | Tommaso Feraco, Enrico Toffalini |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-02-01
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Series: | Frontiers in Psychology |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1433339/full |
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