LLMs produce stable cognitive distortion labels that improve downstream model performance, paired with a kappa-based framework for dataset-agnostic evaluation in subjective NLP tasks.
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cs.CL 2years
2025 2verdicts
UNVERDICTED 2representative citing papers
LLM-enhanced multi-view gated attention MIL framework using ELB decomposition improves cognitive distortion classification on Korean and English therapy datasets.
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Towards Consistent Detection of Cognitive Distortions: LLM-Based Annotation and Dataset-Agnostic Evaluation
LLMs produce stable cognitive distortion labels that improve downstream model performance, paired with a kappa-based framework for dataset-agnostic evaluation in subjective NLP tasks.
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Multi-View Attention Multiple-Instance Learning Enhanced by LLM Reasoning for Cognitive Distortion Detection
LLM-enhanced multi-view gated attention MIL framework using ELB decomposition improves cognitive distortion classification on Korean and English therapy datasets.