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cs.LG2025
A constraints-based approach to fully interpretable neural networks for detecting learner behaviors
Juan D. Pinto, Luc Paquette
The increasing use of complex machine learning models in education has led to concerns about their interpretability, which in turn has spurred interest in developing explainability…
cs.LG2024
Towards a Unified Framework for Evaluating Explanations
Juan D. Pinto, Luc Paquette
The challenge of creating interpretable models has been taken up by two main research communities: ML researchers primarily focused on lower-level explainability methods that suit…