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Related Experiment Video

Updated: Apr 7, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

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Published on: December 6, 2024

Escaping the Jingle-Jangle Jungle: Increasing Conceptual Clarity in Psychology Using Large Language Models.

Dirk U Wulff^1,2, Rui Mata²

¹Max Planck Institute for Human Development, Berlin, Germany.

Current Directions in Psychological Science

|April 6, 2026

Summary

Large language models can help resolve conceptual redundancy in psychology by mapping construct overlap. This computational approach, combined with expert input, aims to clarify psychological terms and definitions for better research.

Keywords:

conceptual clarity embeddings large language models taxonomic incommensurability

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Area of Science:

Psychology
Computational Linguistics
Cognitive Science

Background:

Psychology faces challenges with conceptual redundancy, known as jingle-jangle fallacies.
Inconsistent terminology hinders cumulative knowledge and cross-study comparability.

Purpose of the Study:

To propose using large language models (LLMs) to address conceptual redundancy in psychology.
To create a shared semantic space for psychological constructs.
To systematically map conceptual overlap and clarify construct definitions.

Main Methods:

Utilizing LLMs to place psychological constructs into a unified semantic space.
Developing methods for systematic mapping of conceptual overlap.
Combining computational approaches with expert deliberation.

Main Results:

Demonstrated the potential of LLMs to identify and clarify redundant terminology.
Enabled systematic mapping of conceptual relationships between psychological constructs.
Provided a framework for generating clearer, more precise construct definitions.

Conclusions:

LLMs offer a powerful tool for enhancing conceptual clarity in psychology.
A collaborative effort combining AI with expert judgment is crucial for advancing psychological science.
This approach fosters a more unified and rigorous scientific framework.