RLHF Alignment Case Study
RLHF Alignment Case Study: Evaluating Persona and Factual Accuracy in Large Language Models Objective: Evaluate, rate, and optimize multi-turn LLM responses for style, factual accuracy, and safety constraints. Role: Expert AI Training Specialist & Content Reviewer. Focus Areas: Reinforcement Learning from Human Feedback (RLHF), Prompt Engineering, Fact-Verification, Tone Alignment.