CRPO extends group relative policy optimization with stage-dependent uncertainty modeling and reports a 10.4 percentage point weighted F1 gain over RL baselines across 8 mental health datasets.
Evaluation of ChatGPT for NLP-based mental health applications
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Phi-4 and Gemma-2-9B maintain high intra-model consistency (ICC > 0.89) and ASR robustness for HADS scoring while Llama-3.1-8B degrades sharply, with all models showing score-evidence dissociation.
A multi-view evidential framework combines semantic and reasoning information to improve accuracy and provide trustworthy uncertainty estimates for mental health prediction on text data.
citing papers explorer
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Mental-R1: Aligning LLM Reasoning for Mental Health Assessment
CRPO extends group relative policy optimization with stage-dependent uncertainty modeling and reports a 10.4 percentage point weighted F1 gain over RL baselines across 8 mental health datasets.
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Can We Trust LLMs for Mental Health Screening? Consistency, ASR Robustness, and Evidence Faithfulness
Phi-4 and Gemma-2-9B maintain high intra-model consistency (ICC > 0.89) and ASR robustness for HADS scoring while Llama-3.1-8B degrades sharply, with all models showing score-evidence dissociation.
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Beyond Semantics: An Evidential Reasoning-Aware Multi-View Learning Framework for Trustworthy Mental Health Prediction
A multi-view evidential framework combines semantic and reasoning information to improve accuracy and provide trustworthy uncertainty estimates for mental health prediction on text data.