Natural language boosts LLM performance in coding, planning and robotics

Large language models (LLMs) are becoming increasingly useful for programming and robotics tasks, but for more complicated reasoning problems, the gap between these systems and humans looms large. Without the ability to learn new concepts like humans do, these systems fail to form good abstractions—essentially, high-level representations of complex concepts that skip less-important details—and thus sputter when asked to do more sophisticated tasks.

abstractions coding concepts form gap good humans language language models large language large language models learn llm llm performance llms natural natural language performance planning programming reasoning robotics systems tasks