3 papers
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.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…
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…