Law - U.S. Law - JD/LL.M
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Contributed to a graduate-level U.S. Law data labeling project aimed at improving large language model performance in advanced legal reasoning. Responsibilities included annotating and evaluating model responses to complex legal prompts across jurisprudence, constitutional law, statutory interpretation, international law in U.S. courts, and emerging legal issues (e.g., AI regulation and intellectual property). Labeling tasks involved assessing legal accuracy, reasoning quality, use of doctrine and precedent, alignment with interpretive frameworks, and compliance with predefined rubrics and quality standards. Ensured consistency, precision, and high-quality annotations to support model training and evaluation.
Contributed to a graduate-level U.S. Law data labeling project aimed at improving large language model performance in advanced legal reasoning. Responsibilities included annotating and evaluating model responses to complex legal prompts across jurisprudence, constitutional law, statutory interpretation, international law in U.S. courts, and emerging legal issues (e.g., AI regulation and intellectual property). Labeling tasks involved assessing legal accuracy, reasoning quality, use of doctrine and precedent, alignment with interpretive frameworks, and compliance with predefined rubrics and quality standards. Ensured consistency, precision, and high-quality annotations to support model training and evaluation.
2025