Cognition · Software component
Similarity Exemplar Selector
Software componentCognitionCognition & Memoryarc:SimilarityExemplarSelector
An exemplar selector that retrieves, for each input, the demonstrations most similar to it from the demonstration pool.
Responsibility. Selects per-query demonstrations by similarity to the test input.
Also known as: Similarity-based demonstration retrieval
Variant of Exemplar Selector abstract
When to choose. Choose when accuracy gains justify per-query retrieval cost; computational cost becomes high on large demonstration pools.
Relationships
reads dependency
writes dependency
alternative to variability
Quantitative guidance
As stated by the sources; verify before use.
- Similarity-based selection often outperforms random selection by 8-12 accuracy points (Ch3.5).
Classification
- Patterns
- kNN demonstration retrievalAuto-CoT exemplar matching
- Quality attributes
- Functional suitability: correctness and validity (ISO/IEC 25010 | NIST AI RMF: valid)
Sources
- Ch3.5: T. Nguyen, "Prompt Optimization, Few-Shot Learning, Fine-Tuning," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 3.5. ISBN: 9798244538229.
- Ch5.1: T. Nguyen, "Chain-of-Thought (CoT) Fundamentals," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 5.1. ISBN: 9798244538229.