AI Evaluation & Personalization Review (Project-Based)
Performed AI-generated content evaluation focused on relevance, tone, and personalization quality. Compared multiple model outputs side-by-side and identified subtle differences in clarity, naturalness, and over-explanation. Produced concise rationales for ranking decisions with clear references to specific conversation turns. • Assessed personalization accuracy and detected incorrect personalization or forced inferences • Flagged weak assumptions and unnatural user-context inferences • Wrote structured, turn-referenced justifications for model improvement • Created realistic multi-turn prompts to test contextual understanding and memory handling