Categories of Inference-Time Scaling for Improved LLM Reasoning
Read OriginalThis technical article categorizes and explains inference-time scaling methods used to enhance the reasoning and accuracy of Large Language Models (LLMs). It covers techniques like Chain-of-Thought prompting, self-consistency, and search over solution paths, discussing their implementation and impact based on the author's experiments for a book on building reasoning models.
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