SAGE: Mitigating Long-Horizon Reasoning Biases in LLMs

SAGE introduces Structural Admissibility-Guided Exploration to address exploration and compounding biases in long-horizon reasoning under sparse rewards. The framework uses Symbolic Closure Analysis to provide structural priors that prevent models from following unstable reasoning branches.