A Comprehensive Analysis of Evaluation and Benchmarking Methodologies for Fine-Tuned Large Language Model (LLM)

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 …

Retrieval-Augmented Generation (RAG): A Comprehensive Technical Survey on Bridging Language Models with Dynamic Knowledge

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 …

A Strategic Analysis of LLM Customization: Prompt Engineering, RAG, and Fine-tuning

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 …