Dan Cahn

Optimizing Sparse Outcomes Through Dense Behavioral Signals via Value-Guided Preference Distillation

This work forms a safety framework combining counterfactual user simulation with a validated dialogue-level outcome model to evaluate preference weightings and policy optimization methods, and demonstrates that distilling multi-objective value preferences into the policy via reference-anchored preference optimization m...