{
  "id": 15847,
  "url": "https://arxiv.org/abs/2511.05969",
  "title": "Interpretable Recognition of Cognitive Distortions in Natural Language Texts",
  "summary": "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",
  "authors": "Anton Kolonin, Anna Arinicheva",
  "category": "research",
  "topics": "jobs-economy,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-04T04:00:00.000Z",
  "fetched_at": "2026-08-04T05:10:21.797Z",
  "source_slug": "arxiv-cscy",
  "source_name": "arXiv cs.CY",
  "source_homepage": "https://arxiv.org/list/cs.CY/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/15847",
  "original_url": "https://arxiv.org/abs/2511.05969",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}