papers

Publications (10)

stat.AP2025

VISTA-SSM: Varying and Irregular Sampling Time-series Analysis via State Space Models

Benjamin Brindle, Thomas Derrick Hull, Matteo Malgaroli +1

We introduce VISTA, a clustering approach for multivariate and irregularly sampled time series based on a parametric state space mixture model. VISTA is specifically designed for t…

cs.CL2024

Can AI Relate: Testing Large Language Model Response for Mental Health Support

Saadia Gabriel, Isha Puri, Xuhai Xu +2

Large language models (LLMs) are already being piloted for clinical use in hospital systems like NYU Langone, Dana-Farber and the NHS. A proposed deployment use case is psychothera…

cs.CL2026

Language Markers of Emotion Flexibility Predict Depression and Anxiety Treatment Outcomes

Benjamin Brindle, George A. Bonanno, Thomas Derrick Hull +2

Predicting treatment non-response for anxiety and depression is challenging, in part because of sparse symptom assessments in real-world care. We examined whether passively capture…

cs.CL2026

DIAL: Direct Iterative Adversarial Learning for Realistic Multi-Turn Dialogue Simulation

Ziyi Zhu, Olivier Tieleman, Caitlin A. Stamatis +5

Realistic user simulation is crucial for training and evaluating multi-turn dialogue systems, yet creating simulators that accurately replicate human behavior remains a significant…

cs.CY2026

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…

cs.CY2026

Generative AI Purpose-built for Social and Mental Health: A Real-World Pilot

Thomas D. Hull, Lizhe Zhang, Patricia A. Arean +1

Generative artificial intelligence (GAI) chatbots built for mental health could deliver safe, personalized, and scalable mental health support. We evaluate a foundation model desig…