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Feb, 2024
使用监督、层次概念学习消除硬概念瓶颈模型中的信息泄漏
Eliminating Information Leakage in Hard Concept Bottleneck Models with Supervised, Hierarchical Concept Learning
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Ao Sun, Yuanyuan Yuan, Pingchuan Ma, Shuai Wang
TL;DR
提供标签监督和层次化概念集概念预测模式,SupCBM 消除信息泄漏问题,实现准确预测和解释。
Abstract
concept bottleneck models
(CBMs) aim to deliver interpretable and interventionable predictions by bridging features and labels with human-understandable concepts. While recent CBMs show promising potential, they suffer from
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