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About this paper
Ziyi Zhu, Olivier Tieleman, Caitlin A. Stamatis, Luka Smyth, Thomas D. Hull, Daniel R. Cahn, Jinghong Chen, Matteo Malgaroli
DIAL trains a dialogue-system simulator on real conversations, then revises it iteratively using preference pairs selected by a discriminator distinguishing simulated from real sessions. In mental-health-support conversations, 160K-SFT iteration 2 correlated with real issue rates across 14 chatbot configurations at r = .818, versus .528 before DIAL. DIAL supports offline evaluation, not human testing or safe deployment.
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