AI/LLM Response Rater & Scientific Data Annotator
I evaluated the quality, accuracy, and factuality of generative AI and LLM outputs in scientific and general domains. I performed data annotation tasks focusing on scientific content, fact-checking, hallucination detection, and instruction adherence for AI training purposes. My work included assessing responses for logical consistency, scientific correctness, and coherence across Arabic and English datasets. • Labeled and assessed model outputs for correctness and factuality. • Detected hallucinations and ensured grounded, source-based answers in biology and chemistry. • Validated scientific claims and detected errors in AI-generated responses. • Provided bilingual scientific content evaluation and terminology correction.