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1. Introduction: The Industrialization of RAG The deployment of Large Language Models (LLMs) in enterprise environments has transitioned from a phase of experimental novelty to one of critical infrastructure development. Read More …
Part I: The Paradox of Long Contexts: Expanding Windows, Diminishing Returns The field of Large Language Models (LLMs) is in the midst of a profound architectural transformation, characterized by a Read More …
Part I: The Foundation – From Pre-Training to Specialization The evaluation of a fine-tuned Large Language Model (LLM) is intrinsically linked to the purpose and process of its creation. Understanding Read More …
Part 1: The Customization Triad: A Strategic Framework for LLM Adaptation 1.1 Introduction: Deconstructing the “vs.” The customization of Large Language Models (LLMs) is frequently framed as a choice between Read More …
Introduction to Retrieval-Augmented Generation Defining the RAG Paradigm: Synergizing Parametric and Non-Parametric Knowledge Retrieval-Augmented Generation (RAG) is an artificial intelligence framework designed to optimize the output of a Large Language Read More …
The LLM Customization Spectrum: Core Principles and Mechanisms The deployment of Large Language Models (LLM) within the enterprise marks a significant technological inflection point. However, the true value of these Read More …