4 papers
Engagement Intensity as a Learner-Modeling Signal for Adaptive AI Ethics Instruction
Yongkyung Oh, Lynn Talton, Alex Bui
Adaptive AI ethics instruction in graduate research training benefits from intake measures that reflect differences in prior LLM experience. Prior coursework or workshop attendance…
Silent Failures in Federated Personalization of Foundation Models
YongKyung Oh, Alex Bui
Foundation models are increasingly personalized on decentralized private data through federated learning and are now deployed at scale under growing regulatory requirements for pos…
Position: State-of-the-Art Claims Require State-of-the-Art Evidence
YongKyung Oh
State-of-the-Art (SOTA) claims pervade Artificial Intelligence (AI) and Machine Learning (ML) research. These claims rest on benchmark evaluations, where models are ranked by aggre…
Survey-aware Machine Learning: A Guideline for Valid Population Health Inference based on Scoping Review
YongKyung Oh, Henry W. Zheng, Jeffrey Feng +1
Machine Learning (ML) models trained on complex health surveys such as the National Health and Nutrition Examination Survey (NHANES) often ignore primary sampling units, stratifica…