SST trains models to produce concise sufficient reasons as an extra output, yielding faster and often smaller explanations than post-hoc methods like Anchors and SIS.
We acknowledge, however, that despite the difficulty of theMSR query being established through a reduction from the Shortest Implicant Core problem (as proven in Barceló et al
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Explain Yourself, Briefly! Self-Explaining Neural Networks with Concise Sufficient Reasons
SST trains models to produce concise sufficient reasons as an extra output, yielding faster and often smaller explanations than post-hoc methods like Anchors and SIS.