14 citations · 16 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
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…
CyclicJudge: Mitigating Judge Bias Efficiently in LLM-based Evaluation
Ziyi Zhu, Olivier Tieleman, Alexey Bukhtiyarov +1
LLM-as-judge evaluation has become standard practice for open-ended model assessment; however, judges exhibit systematic biases that cannot be averaged out by increasing the number…
Beyond Simulations: What 20,000 Real Conversations Reveal About Mental Health AI Safety
Caitlin A. Stamatis, Jonah Meyerhoff, Richard Zhang +3
Mental-health AI safety is typically evaluated with small, simulation-based benchmarks that may not reflect the linguistic and contextual diversity of deployment. We pair four benc…