Confidence Score
A probabilistic estimate a model gives of the correctness of its own output, typically generated from model logprobs, multi-model voting, or a dedicated verification model, used for decision threshold judgments in AI governance.
Timeline (last 90 days)
In continual learning, standard confidence scores shift systematically as tasks progress: the model is overconfident on inputs from recent tasks and gives muddled confidence for old tasks and truly unknown inputs.
A confidence score is the model's quantitative assessment of the reliability of its own answer, usually generated by the model or computed by an additional model; a low confidence score can trigger human review or a downgraded response to avoid error propagation.
In an Agentic IDP system, the Agent usually gives a confidence score for each extracted field, which may come from model token probabilities, the consistency of results from multiple extraction tools, or the degree of agreement with business rules.
The output of an object detection model usually contains three elements: label, bounding box, and confidence score; the core difference from image classification is that object detection also needs to locate the object's specific position in the image.
'信任恒温器'方案中，每个决策带有基于原则测得的置信度分数，高于阈值则自动执行，低于阈值则人工介入，人的判断被反馈进学习回路。
Confidence values typically originate from the model's softmax probability distribution over each option — a large probability gap yields a high confidence value, while a uniform distribution yields a low one.
Each inference an agent makes about user preferences is accompanied by a confidence score between 0 and 1 that is dynamically updated as new evidence arrives, embodying the idea of Bayesian reasoning.
All Facts (7)
In continual learning, standard confidence scores shift systematically as tasks progress: the model is overconfident on inputs from recent tasks and gives muddled confidence for old tasks and truly unknown inputs.
50%UnverifiedA confidence score is the model's quantitative assessment of the reliability of its own answer, usually generated by the model or computed by an additional model; a low confidence score can trigger human review or a downgraded response to avoid error propagation.
50%UnverifiedIn an Agentic IDP system, the Agent usually gives a confidence score for each extracted field, which may come from model token probabilities, the consistency of results from multiple extraction tools, or the degree of agreement with business rules.
50%UnverifiedThe output of an object detection model usually contains three elements: label, bounding box, and confidence score; the core difference from image classification is that object detection also needs to locate the object's specific position in the image.
50%Unverified'信任恒温器'方案中，每个决策带有基于原则测得的置信度分数，高于阈值则自动执行，低于阈值则人工介入，人的判断被反馈进学习回路。
50%UnverifiedConfidence values typically originate from the model's softmax probability distribution over each option — a large probability gap yields a high confidence value, while a uniform distribution yields a low one.
50%UnverifiedEach inference an agent makes about user preferences is accompanied by a confidence score between 0 and 1 that is dynamically updated as new evidence arrives, embodying the idea of Bayesian reasoning.
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