Large Language Models (LLMs) have demonstrated remarkable capabilities in fluent text generation, code synthesis, and contextual translation. However, their core architecture relies on autoregressive next-token prediction, which fundamentally struggles with complex reasoning tasks. Specifically, deep logical paradoxes and self-referential logic ...