Applied AI evaluation workflow and structured LLM assessment (projects: LLM Response Ranking & Preference Study; Hallucination & Factual Integrity Audit Set; Prompt Sensitivity & Output Variance Testing)
Performed structured AI evaluation and rubric-based scoring of LLM outputs, including pairwise response ranking and instruction-following verification. Detected hallucinations and unsupported claims by isolating violations, verifying logical grounding against provided constraints, and classifying severity. Documented justification logs and correction-oriented feedback notes to ensure auditability, repeatability, and defensible decisions. • Pairwise ranking across reasoning, factuality, and instruction-following prompt categories • Multi-dimension rubric scoring (factual accuracy, reasoning validity, instruction adherence, completeness) • Hallucination and unsupported claim detection with traceability checks • Structured evaluation logs and prompt-iteration notes for reproducibility