DKC-LLM: Dynamic Knowledge Caching for Large Language Models in Business Applications — Khaliq & Adebayo (2026)

1 More Paper · Sep 26, 2026 · 1h 20m · transcript

Large Language Models (LLMs) often face severe latency and computational cost constraints which hinder their adoption in real-time enterprise applications. Retrieval-Augmented Generation (RAG) frameworks, while improving factual accuracy, further increase inference delays owing to additional retrieval and context integration steps. To address these challenges, we propose Dynamic Knowledge Caching for Large Language Models (DKC-LLM), a novel framework that integrates dynamic semantic caching with an adaptive cache management strategy, which detects and compensates for semantic drift to…