Adversarial Training Improves User Simulation for Mental Health Dialogue Systems

This research investigates adversarial training to create more robust user simulations for mental health dialogue systems, a crucial area for improving the reliability and safety of such tools. The study's focus on failure sensitivity highlights the importance of anticipating and mitigating potential negative interactions in sensitive therapeutic contexts.

• •Applies adversarial training to user simulation, a novel approach for mental health dialogue systems.
• •Addresses the need for failure-sensitive models to handle potentially harmful outputs.
• •Focuses on improving the reliability and safety of AI-driven mental health support tools.