5 papers
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…
Multi-Objective Alignment of Language Models for Personalized Psychotherapy
Mehrab Beikzadeh, Yasaman Asadollah Salmanpour, Ashima Suvarna +4
Mental health disorders affect over 1 billion people worldwide, yet access to care remains limited by workforce shortages and cost constraints. While AI systems show therapeutic pr…
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…
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…
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…