Researchers studied the gap between planning and execution in large language models (LLMs) and proposed a new approach called Planning-as-Routing, which uses a deterministic router to dispatch tasks to pattern-specific executors based on planning modes. The study found that pattern-specific executors improve task success and close the execution gap, but mode selection remains a challenge.