Interpretable Recognition of Cognitive Distortions in Natural Language Texts
arXiv:2511.05969v2 Announce Type: replace-cross 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 rec
Record details
Published: 4 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Jobs & economy · Transparency
Retrieved: 4 August 2026
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ethics.ai (4 August 2026), “Interpretable Recognition of Cognitive Distortions in Natural Language Texts,” evidence record 15847, https://ethics.ai/record/15847 (originally published by arXiv cs.CY).
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