Controlling Reasoning Effort in LLMs

AI Summary

Researchers have discovered that large language models can be trained to operate in different reasoning modes, adjusting their computational effort from low to high depending on task complexity. This capability allows LLMs to allocate resources more efficiently by performing quick reasoning for simple problems while engaging deeper analysis for challenging queries.