Reciprocal Co-Training (RCT): Coupling Gradient-Based and Non-Differentiable Models via Reinforcement Learning

This work introduces a reciprocal co-training framework that couples a Large Language Model (LLM) with a Random Forest (RF) classifier via reinforcement learning. It creates an iterative feedback loop where each model improves using signals from the other, demonstrating consistent performance gains across medical datasets.