Sebastian Raschka • 1/24/2026

Categories of Inference-Time Scaling for Improved LLM Reasoning

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This technical article categorizes and explains inference-time scaling methods used to enhance the reasoning and accuracy of large language models (LLMs). It discusses techniques such as chain-of-thought prompting, self-consistency, and rejection sampling, based on the author's research and experimentation for a book on building reasoning models. The content is aimed at practitioners and researchers in AI and machine learning.

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#llm #Reasoning #Inference Scaling
Categories of Inference-Time Scaling for Improved LLM Reasoning

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