A lightweight RL policy over a 25-dimensional latent student state and four high-level tutor actions improves simulated tutoring success rates over prompt engineering, but fails to generalize to new math problems.
Tutor:" and the sixth-grade student’s utterances are pref- aced by “Student:
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Efficient RL for optimizing conversation level outcomes with an LLM-based tutor
A lightweight RL policy over a 25-dimensional latent student state and four high-level tutor actions improves simulated tutoring success rates over prompt engineering, but fails to generalize to new math problems.