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Causal Neural Probabilistic Circuits
融合概念瓶颈与因果概率电路，支持测试时人工干预，提升模型可解释性与预测准确度。
arXiv:2603.01372v2 Announce Type: replace-cross Abstract: Concept Bottleneck Models (CBMs) enhance the interpretability of end-to-end neural networks …
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Towards Fine-Grained and Verifiable Concept Bottleneck Models
概念瓶颈模型新框架，实现细粒度视觉证据定位与可验证性，提升可解释AI可靠性
arXiv:2605.14210v1 Announce Type: cross Abstract: Concept Bottleneck Models (CBMs) offer interpretable alternatives to black-box predictors by introdu…