# Advanced Caching Strategies & SCR Pipeline

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To maximize reasoning efficiency, minimize inference costs, and enable dynamic knowledge integration for Tiny LLMs, the KCG+CAG architecture incorporates advanced caching strategies enhanced by Selective Contextual Reasoning (SCR) pipelines.

# Selective Contextual Reasoning (SCR)

Inspired by state-of-the-art research (arXiv:2503.05212), SCR enables Tiny LLMs to perform lightweight, dynamic reasoning over external knowledge caches without modifying model weights.

• Step 1: Semantic Retrieval - Retrieve relevant knowledge entries from the KV-cache and semantic graph indexes.
• Step 2: Confirmation and Filtering - Tiny LLMs or Gateways filter, confirm, and deduplicate retrieved entries, ensuring contextual fit and factual accuracy.
• Step 3: Contextual Reasoning - Construct an enriched prompt using confirmed knowledge, allowing Tiny LLMs to perform high-quality reasoning locally.
• Step 4: Fallback to DoD and Big LLMs - Only if SCR fails or lacks confidence, a DoD escalation is triggered.

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