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CAST: Game Solvers as Turn-Level Teachers for LLM Agents

27 upvotes · 28 JUL 2026 · Yu Wang, Yi-Kai Zhang, Wentao Shi et al.

This paper proposes a method to improve reinforcement learning with verifiable rewards by using game solvers to provide turn-level credit to agents, allowing them to learn more effectively. Practitioners might care about this approach because it could lead to more robust and efficient AI decision-making.

reinforcement learningverifiable rewardsgame solversturn-level signalsprocess signalscontinual learning