Pablo Agustin Quemas developed and integrated the CareQA benchmark dataset for healthcare question answering into both the red-hat-data-services/lm-evaluation-harness and swiss-ai/lm-evaluation-harness repositories. He designed the benchmark to support both multiple-choice and open-ended formats in English and Spanish, enabling nuanced evaluation of language models on medical queries. Using Python and YAML, Pablo implemented comprehensive metrics including BLEU, ROUGE, BERTScore, and perplexity, allowing for detailed model assessment. His work demonstrated strong skills in benchmark development and data engineering, ensuring consistent feature propagation and accelerating cross-team adoption for multilingual, multi-format healthcare QA evaluation across two major codebases.