Category:

AI Reliability & Evaluation

Definition

Systems that estimate how confident an LLM is in its own answer.

Explanation

Confidence scoring measures the likelihood that an LLM’s output is correct. It helps enterprises detect uncertain or risky answers before they reach users. Scores may be based on log probabilities, self-evaluation prompts, retrieval strength, ensemble agreement, or verification outcomes. Confidence scoring is critical for safety, compliance, and agent decision-making.

Technical Architecture

LLM Output → Confidence Engine → Threshold Check → Deliver / Verify / Reject

Core Component

Probability scores, verifier model, metadata confidence, retrieval strength

Use Cases

Enterprise copilots, regulated industries, analytics assistants

Pitfalls

LLMs are poorly calibrated; confidence does not always match correctness

LLM Keywords

Confidence Scoring, LLM Uncertainty, Output Calibration

Related Concepts

Related Frameworks

• Self-Verification
• Hallucination Mitigation
• Evaluation

• Confidence Scoring Pipeline

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