Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2026)
Jan 1, 2026
McMasters of Change: Predicting Well-Being States and Transitions from Longitudinal Language
Jan 1, 2026
Examining the Utility of Self-disclosure Types for Modeling Annotators of Social Norms
Jan 1, 2026
Evaluating Document-Tuned Transformer Representations for Person-level Mental Health Assessment
Jan 1, 2026
Capturing Human Cognitive Styles with Language: Towards an Experimental Evaluation Paradigm
Jul 12, 2025
Who We Are, Where We Are: Mental Health at the Intersection of Person, Situation, and Large Language Models
Jan 1, 2025
Systematic Evaluation of Auto-Encoding and Large Language Model Representations for Capturing Author States and Traits
Jan 1, 2025
Linking Language-based Distortion Detection to Mental Health Outcomes
Jan 1, 2025
From Text to Context: Contextualizing Language with Humans, Groups, and Communities for Socially Aware NLP
Jan 1, 2024
Archetypes and Entropy: Theory-Driven Extraction of Evidence for Suicide Risk
We combined theory-driven suicidal archetypes with language models and relative entropy to identify suicide risk in text. The combined approach outperformed individual methods, achieving high accuracy in shared task evaluations. Our findings suggest that integrating theoretical and data-driven methods is crucial for mental health analysis, outperforming prompt-based approaches.
Jan 1, 2024