Large Language Models (LLMs) have shown remarkable abilities, but they often struggle with complex logical reasoning. Think of them as eloquent speakers who sometimes miss the logical connections. A new research paper introduces LLM-ARC, a system designed to address this weakness by incorporating an "Automated Reasoning Critic" (ARC). Imagine an LLM trying to write a logical argument, and a strict but helpful critic constantly checks its work. That's LLM-ARC in a nutshell. This system uses a method called "Actor-Critic," where the LLM acts as the "actor," attempting to write logical code (like a set of rules) and even creating tests to see if its code makes sense. The ARC then plays the role of the "critic," rigorously evaluating the LLM's code and tests. If the tests fail, the critic provides detailed feedback, and the LLM revises its work based on that feedback. This back-and-forth process repeats until the LLM’s logic holds up to scrutiny. The researchers tested LLM-ARC on a challenging logical reasoning benchmark called FOLIO and achieved a remarkable 88.32% accuracy, surpassing existing state-of-the-art methods. One exciting aspect of this research is the use of test generation. The LLM not only writes the logical code but also generates tests, similar to how software developers ensure their programs function correctly. This addition significantly boosts performance, proving the value of self-critique. Moreover, training the LLM on the entire process of code creation, testing, feedback, and revision leads to the best results. It’s like giving the LLM a crash course in logical thinking. While this research shows significant progress, challenges remain. LLMs still struggle with certain types of logical statements, particularly those involving multiple variables or the nuanced distinction between types and instances (like distinguishing a general concept from a specific example). These limitations highlight the need for ongoing research. This work opens up exciting possibilities. Imagine AI systems that can not only generate text but also build robust logical arguments, design complex plans, and reason through intricate scenarios. This could revolutionize fields like law, medicine, and finance, where precise logical reasoning is paramount. LLM-ARC represents a significant step toward achieving this vision, bringing us closer to truly intelligent AI systems.