Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

arXiv:2404.02575v1 Announce Type: new
Abstract: Algorithmic reasoning refers to the ability to understand the complex patterns behind the problem and decompose them into a sequence of reasoning steps towards the solution. Such nature of algorithmic reasoning makes it a challenge for large language models (LLMs), even though they have demonstrated promising performance in other reasoning tasks. Within this context, some recent studies use programming languages (e.g., Python) to express the necessary logic for solving a given instance/question (e.g., Program-of-Thought) as …

abstract arxiv challenge compilers cs.cl language language models large language large language models llms nature patterns reasoning solution them type