Interpretable Recognition of Cognitive Distortions in Natural Language Texts

arXiv:2511.05969 · cs.CL, cs.AI, cs.CY, cs.LG · Submitted 2025-11-08 · Read on arXiv

cs.CL, cs.AI, cs.CY, cs.LG

Submitted: 2025-11-08

Updated: 2026-09-12

Comments: 16 pages, 10 figures

Code: https://github.com/aigents/pygents

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Interpretability — 15× in this paper · explained in 15 episodes
Core — 3× in this paper · explained in 2 episodes
Embeddings — 3× in this paper · explained in 2 episodes
Feature Selection — 3× in this paper · explained in 4 episodes
Personalization — 3× in this paper · explained in 2 episodes
Accuracy — 2× in this paper · explained in 1 episode
Explainability — 2× in this paper · explained in 3 episodes
Annotation Ambiguity — 1× in this paper · explained in 1 episode
Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
Benchmark — 1× in this paper · explained in 2 episodes
Consistency — 1× in this paper · explained in 3 episodes
Decode — 1× in this paper · explained in 2 episodes
F1 Score — 1× in this paper · explained in 3 episodes
Fine-Tuning — 1× in this paper · explained in 5 episodes
Generalization — 1× in this paper · explained in 13 episodes
Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
Robustness — 1× in this paper · explained in 5 episodes
Sparsity — 1× in this paper · explained in 4 episodes
Tokenization — 1× in this paper · explained in 2 episodes
Transformer — 1× in this paper · explained in 2 episodes

Sources

Related papers