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arXiv AI By Shouang Wei, Min Zhang, Xin Lin, Bo Jiang, Kun Kuang, Zhongxiang Dai

UCO: A Multi-Turn Interactive Reinforcement Learning Method for Adaptive Teaching with Large Language Models

Read the original on arXiv AI →

The paper introduces UCO, a multi‑turn interactive reinforcement learning method designed to improve adaptive teaching with large language models. UCO employs two reward functions—Progress Reward to gauge genuine cognitive advancement and Scaffold Reward to keep instruction within each student’s Zone of Proximal Development. Experiments on BigMath and MathTutorBench show UCO outperforming 11 baseline models and matching advanced closed‑source systems.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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