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20232026
most citedBeyond Simulations: What 20,000 Real Conversations Reveal About Mental Health AI Safety

2 citations · 4 across the 10 of their papers we have counts for

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Showing 2026Show all

8 papers · 1 filter

cs.CL2026

Optimizing Sparse Outcomes Through Dense Behavioral Signals via Value-Guided Preference Distillation

Ziyi Zhu, Daniel R. Cahn, Thomas D. Hull +4

Aligning multi-turn dialogue agents is usually framed as matching turn-level human preferences, yet direct optimization of long-term outcomes is often ineffective and prone to rewa…

cs.HC2026

Healthcare Utilization, Chronic Condition Management, and Workplace Functioning Among Users of a Purpose-Built Mental Health AI (Ash): Cross-Sectional Study

Kristen M. Van Swearingen, Thomas D. Hull, Jeffrey Swigert +1

Mental health challenges can exacerbate physical symptoms and complicate management of chronic conditions. Purpose-built artificial intelligence (AI) tools may offer scalable suppo…

cs.HC2026

Engagement Phenotypes for a Sample of 102,684 AI Mental Health Chatbot Users and Dose-Response Associations with Clinical Outcomes

Emma C. Wolfe, Ting Su, Olivier Tieleman +3

Background: Conversational AI chatbots are emerging as scalable mental health tools, but little is known about real world engagement or its relationship to clinical outcomes. Objec…

cs.HC2026

Functional outcomes and naturalistic engagement with a purpose-built conversational AI for mental health (Ash)

Kristen M. Van Swearingen, Thomas D. Hull, Karthik V. Sarma +1

Background: Conversational AI chatbots designed for mental health may offer an accessible, scalable avenue for supporting psychological well-being, yet prior evaluations have large…

cs.CL2026

Fine-tuning LLMs for Passive Depression Severity Estimation from AI Mental Health Dialogue

Olivier Tieleman, Ziyi Zhu, Ting Su +3

Depression is the leading cause of disability worldwide, and early detection of symptom change is essential for timely intervention. Validated instruments such as the Patient Healt…

cs.HC2026

Talking to a Human as an Attitudinal Barrier: A Mixed Methods Evaluation of Stigma, Access, and the Appeal of AI Mental Health Support

Caitlin A. Stamatis, Emma C. Wolfe, Matteo Malgaroli +1

Background: Many people who could benefit from therapy do not receive it. Conversational AI is increasingly used for mental health support, yet it is unclear which barriers AI help…