This comprehensive survey examines various Large Language Model (LLM) alignment techniques used to ensure model outputs align with human intentions. It provides a detailed analysis of methodologies including Reinforcement Learning from Human Feedback (RLHF), Reinforcement Learning from AI Feedback (RLAIF), Proximal Policy Optimization (PPO), and Direct Preference Optimization (DPO).