AIBullisharXiv – CS AI · 14h ago6/10
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Learn from A Rationalist: Distilling Intermediate Interpretable Rationales
Researchers propose REKD (Rationale Extraction with Knowledge Distillation), a method that improves the interpretability and performance of smaller deep neural networks by having them learn from larger teacher models' rationales and predictions. The approach demonstrates significant performance gains across language and vision tasks, offering a practical framework for making AI systems more transparent and verifiable in high-stakes applications.