Mental Health AI

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• Published Subscription Original Research 20 Jul 2026

  Reward-Aligned Reinforcement Learning from Human Feedback for Emotion-Sensitive Large Language Model Therapists: Balancing Empathetic Engagement, Boundary Safety, and Clinical Accountability

  By Vaibhav Baishkhiyar, Ankit Kumar Tiwari, Hardik Srivastava, Shikhar Gupta

  Abstract: The deployment of large language models (LLMs) in mental health therapy contexts introduces a critical alignment challenge: these systems must simultaneously cultivate genuine empathic rapport, observe clinically grounded safety boundaries, and remain auditable under institutional accountability frameworks. Existing reinforcement learning from human feedback (RLHF) pipelines optimize for a scalar reward signal that is demonstrably insufficient for the multi-objective, temporally extended nature of therapeutic conversation. This paper presents RA-RLHF-T (Reward-Aligned RLHF …

  Published in International Journal of Tropical Medicines · Vol. 3, Issue 2, 2026 Read article →