The Mechanics of Alignment: A Comprehensive Analysis of RLHF, Direct Preference Optimization, and Parameter-Efficient Architectures in Large Language Models

1. Introduction: The Post-Training Paradigm and the Alignment Challenge The contemporary landscape of artificial intelligence has been irrevocably altered by the emergence of Large Language Models (LLMs) trained on datasets Read More …

The Mechanics of Alignment: A Comprehensive Analysis of RLHF, Direct Preference Optimization, and Parameter-Efficient Architectures in Large Language Models

1. Introduction: The Post-Training Paradigm and the Alignment Challenge The contemporary landscape of artificial intelligence has been irrevocably altered by the emergence of Large Language Models (LLMs) trained on datasets Read More …

The Evolution of LLM Alignment: A Technical Analysis of Instruction Tuning and Reinforcement Learning from Human Feedback

Part 1: The Alignment Problem: From Next-Word Prediction to Instruction Following 1.1 Executive Summary: The Alignment Trajectory The development of capable and safe Large Language Models (LLMs) follows a well-defined, Read More …

The Architecture of Alignment: A Technical Analysis of Post-Training Optimization in Large Language Models

The Post-Training Imperative: From General Competence to Aligned Behavior The Duality of LLM Training: Pre-training for Capability, Post-training for Alignment The development of modern Large Language Models (LLMs) is characterized Read More …