Box Maze: A Process-Control Architecture for Reliable LLM Reasoning

ArXi:2603.19182v1 Announce Type: new Large language models (LLMs) nstrate strong generative capabilities but remain vulnerable to hallucination and unreliable reasoning under adversarial prompting. Existing safety approaches -- such as reinforcement learning from human feedback (RLHF) and output filtering -- primarily operate at the behavioral level and may lack explicit architectural mechanisms for enforcing reasoning process integrity.