Safety & Security · Software component
Cascaded Fact Checker
Software componentSafety & SecuritySafety, Security & Governancearc:CascadedFactChecker
A fact checking rail that runs alignment scoring on all responses, escalates marginal-confidence cases to NLI verification and only ambiguous residue to self-check LLM critique.
Responsibility. Minimizes fact-checking cost while maximizing hallucination catch rate through confidence-based escalation.
Variant of Fact Checking Rail abstract
When to choose. Choose for production deployments needing the lowest hallucination rate at mostly-minimal added latency.
Relationships
invokes dependency
alternative to variability
Design guidance
- SHOULD invoke NLI only for marginal alignment confidence (0.4-0.6) and self-check LLM only for the ambiguous remainder (<5%).
Quantitative guidance
As stated by the sources; verify before use.
- Most requests add 45ms, edge cases add 150ms; hallucination rate below 2% (Ch7.1A).
Classification
- Patterns
- Confidence-tiered verification cascade
- Quality attributes
- Functional suitability: correctness and validity (ISO/IEC 25010 | NIST AI RMF: valid)Cost efficiency
Sources
- Ch7.1A: T. Nguyen, "Advanced Implementation with Nvidia NEMO Framework and Nvlink," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 7.1A. ISBN: 9798244538229.