2026
Learning for Highly Faithful Explainability
ICLR 2026poster
Learning to Explain is a forward-looking paradigm recently proposed in the field of explainable AI, which envisions training explainers capable of producing high-quality explanations for target models efficiently. Although existing studies have made attempts through self-supervised optimization or l…