Reasoning Module

Reasoning modules are computational components designed to enhance the logical capabilities of artificial intelligence systems, particularly large language models (LLMs), which often struggle with complex reasoning tasks. Current research focuses on improving the faithfulness and efficiency of reasoning processes, employing methods like chain-of-thought prompting, iterative cognitive tree construction, and modular architectures that combine neural networks with symbolic reasoning or external knowledge bases. These advancements aim to create more robust and interpretable AI systems capable of handling nuanced reasoning tasks across diverse domains, such as question answering, mathematical problem-solving, and even visual reasoning in applications like video prediction.