From Stochastic Answers to Verifiable Reasoning: Interpretable Decision-Making with LLM-Generated Code

ArXi:2603.13287v1 Announce Type: cross Large language models (LLMs) are increasingly used for high-stakes decision-making, yet existing approaches struggle to reconcile scalability, interpretability, and reproducibility. Black-box models obscure their reasoning, while recent LLM-based rule systems rely on per-sample evaluation, causing costs to scale with dataset size and