Preprint
Jul 2026
LLM-as-a-Tutor: Policy-Aware Prompt Adaptation for Non-Verifiable RL
LLM-as-a-Tutor is introduced, a framework that extends the LLM's role from judge to tutor: a single model serves as an examiner that pairwise-compares policy rollouts to detect non-challenging prompts, and as a generator that appends atomic constraints to them.
Yujin Kim, Namgyu Ho, Sangmin Hwang et al.
· 0 citations