Artificial intelligence is rapidly advancing, particularly in its reasoning capabilities, which could make AI a dependable partner in critical areas such as scientific research and healthcare. To enhance these reasoning abilities, three main strategies have been identified: improving architectural design to enhance performance in smaller models, integrating mathematical reasoning techniques for increased reliability, and developing stronger generalization capabilities to apply reasoning across various domains. Smaller language models face challenges in continuous learning and refining their understanding due to limited capacity, making robust reasoning more difficult. Despite the potential of large language models trained on extensive world knowledge, they struggle with continuous learning. These advancements aim to create more intelligent reasoning systems, even in smaller models, paving the way for more versatile and reliable AI applications.

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