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Prompt + Response Writing (SFT)I have experience contributing to AI training data development through the creation of high-quality, multimodal evaluation datasets for vision-language models. In this role, I authored challenging visual and compositional reasoning questions based on real-world charts, graphs, and diagrams, ensuring each question had a verified and accurate answer. My work focused on testing a model’s ability to interpret visual information, reason across multiple data elements, and accurately answer complex chart-based questions. This experience strengthened my skills in data annotation, quality assurance, analytical reasoning, and dataset creation for machine learning applications. I developed a strong attention to detail when validating answers and designing questions that measure higher-order reasoning rather than simple data extraction. My background in analyzing quantitative information, combined with experience creating benchmark datasets for AI evaluation, allows me to contribute effectively to projects involving data labeling, model assessment, and training data generation.
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ClassificationFellows will author challenging visual and compositional reasoning questions (with verified answers) over real-world charts to support multimodal vision-language model development. The goal is to benchmark model performance in chart and diagram question answering.
Bachelors, Accounting
Audit Intern
Consulting Intern
