Youmi Suk

Distilling Black-Box Machine Learning into a Small, Self-Explaining Language Model for Learning Analytics

A two-stage fine-tuning pipeline is proposed that distills a fitted black-box estimator and its post hoc interpretation into a small, open-weight large language model (LLM) that returns an individual-level estimate and explains in natural language that predicts and explains offline on a commodity laptop, so student records never leave the machine.