Interpretable Recognition of Cognitive Distortions in Natural Language Texts

📝 Original Info

• Title: Interpretable Recognition of Cognitive Distortions in Natural Language Texts
• ArXiv ID: 2511.05969
• Date: 2025-11-08
• Authors: ** 논문에 저자 정보가 제공되지 않았습니다. (저자명, 소속, 연락처 등은 원문을 확인해 주세요.) **

📝 Abstract

We propose a new approach to multi-factor classification of natural language texts based on weighted structured patterns such as N-grams, taking into account the heterarchical relationships between them, applied to solve such a socially impactful problem as the automation of detection of specific cognitive distortions in psychological care, relying on an interpretable, robust and transparent artificial intelligence model. The proposed recognition and learning algorithms improve the current state of the art in this field. The improvement is tested on two publicly available datasets, with significant improvements over literature-known F1 scores for the task, with optimal hyper-parameters determined, having code and models available for future use by the community.

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