Cognition · Model asset

Verifier Model

Model assetCognitionCognition & Memoryarc:VerifierModel

Model weights fine-tuned on labeled correct and incorrect reasoning steps to judge reasoning correctness in a specific domain.

Responsibility. Encodes learned domain-specific judgments of reasoning-step correctness.

Also known as: Fine-tuned verifier

Direct neighbourhood (hover for relationship types)

Relationships

deployed on structural

Inference Server Ch3.6

is trained by lifecycle

Fine-Tuning Pipeline abstract Ch3.6

Design guidance

SHOULD be trained on high-quality annotations explaining why steps are correct or incorrect, optionally mixed with synthetic data with known labels.

Quantitative guidance

As stated by the sources; verify before use.

Healthcare case: additional training data raised detection of hallucinated symptoms to 94% (Ch3.6).

Classification

Quality attributes: Functional suitability: correctness and validity (ISO/IEC 25010 | NIST AI RMF: valid)

Sources

Ch3.6: T. Nguyen, "Trace Analysis and Execution Debugging," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 3.6. ISBN: 9798244538229.