2026
Learn from A Rationalist: Distilling Intermediate Interpretable Rationales
ICML 2026poster
Because of the pervasive use of deep neural networks (DNNs), especially in high-stakes domains, the interpretability of DNNs has received increased attention. The general idea of rationale extraction (RE) is to provide an interpretable-by-design framework for DNNs via a select-predict architecture w…