Open-source research
AMBER
An adaptive meta-balancing framework for integrating heterogeneous graph signals in knowledge tracing.
- Year
- 2025
- Status
- active
- Focus
- Python · Graph Learning · Knowledge Tracing
What it does
AMBER tackles imbalance between heterogeneous graph views used to model student learning. A pretrained dual-graph teacher provides ensemble knowledge while a meta-distillation mechanism adjusts the teacher according to student-model feedback.
The official implementation includes the model, preprocessing utilities, and experiment configuration used for the CIKM 2025 study.
Evidence and scope
This page is a concise guide to the work. Use the primary paper for the experimental setup, quantitative results, limitations, and formal claims; use the repository for the implementation and current reproduction instructions.