Categories of Inference-Time Scaling for Improved LLM Reasoning

Inference-time scaling allows large language models to produce better, more accurate answers by using additional computing power during text generation rather than requiring more training. Major LLM providers now use these techniques, which include methods like chain-of-thought prompting, self-consistency checking, and solution path searching to improve model performance without changing underlying weights.