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Steering reasoning effort in language models
Research shows how to control how much 'thinking' a language model uses on different tasks, allowing it to allocate resources efficiently. This is about adjusting the model's internal processes to match the complexity of the problem.
WHY IT MATTERS
The ability to vary reasoning effort can make AI systems both cheaper to run and faster on simple tasks, while retaining the ability to solve complex problems when needed.
SOURCES
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