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 …

Long-Horizon Planning and Autonomous Reliability in Agentic AI Systems: A 2025 State-of-the-Art Analysis

1. Executive Summary: The Agentic Pivot of 2025 The trajectory of artificial intelligence has undergone a fundamental phase shift in 2025. The industry has moved decisively beyond the “generative” era—characterized 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 …

Codifying Intent: A Technical Analysis of Constitutional AI and the Evolving Landscape of AI Alignment

Executive Summary The rapid advancement of artificial intelligence (AI) has elevated the challenge of ensuring these systems operate in accordance with human intentions from a theoretical concern to a critical Read More …

The Synthetic Data Paradox: A Comprehensive Analysis of Safety, Risk, and Opportunity in LLM Training

Section 1: The New Data Paradigm: An Introduction to Synthetic Data Generation The development of large language models (LLMs) has been fundamentally constrained by a singular resource: high-quality training data. 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 …