Large language models (LLMs) have revolutionized artificial intelligence by demonstrating remarkable capabilities in text generation and problem-solving. However, a critical limitation persists in their default “fast thinking” approach—generating outputs based on a single query without iterative refinement. While recent “slow thinking” methods like chain-of-thought prompting break problems into smaller steps, they remain constrained by static […]
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