Deep thinking assurance programs for key decision-making scenarios
For important scenarios such as business decision-making and healthcare consulting, ensuring that models think in sufficient depth requires multiple layers of safeguards:
- Doublethink validation: set >20 seconds min-think-time to force full thinking
- Visualization of the reasoning process: real-time monitoring of model thought paths and token usage
- tight control over parameters:: Low temperature (0.3-0.5) and high top-p (0.9-1.0) were used.
Implementation Steps:
- Add -min-think-time 20 to the startup parameters
- Use -top-p 0.95 to ensure that most of the possible options are covered
- Explicitly ask for a list of pro and con arguments in the prompt
- Perform multiple rounds of validation tests on the output
Industry-specific advice:
- Financial analysis: models are required to show data sources and calculations
- Medical advice: mandatory modeling to cite authoritative medical literature
- Application of the law: the relevant legal basis must be indicated
It is also recommended that a manual review mechanism be established for secondary validation of key outputs.
This answer comes from the articleR1 Overthinker: Forcing DeepSeek R1 Models to Think LongerThe
May not be reproduced without permission:AI productivity tools " How to prevent DeepSeek R1 from thinking shallowly in important decision-making scenarios?
