AI Output Evaluation & Benchmarking
Benchmarked and evaluated AI-generated summaries for alignment with manual outputs. Identified hallucinations, gaps in context, and inconsistencies in AI outputs. Documented error patterns to improve future model prompting and evaluation. • Compared machine-generated summaries to human-written text. • Detected logical inaccuracies and reasoning errors. • Provided feedback to enhance model accuracy. • Used tools like ChatGPT and Claude for analysis and review.