NEURIPS 2025 "concept bottleneck models" Papers
6 papers found
An Analysis of Concept Bottleneck Models: Measuring, Understanding, and Mitigating the Impact of Noisy Annotations
Seonghwan Park, Jueun Mun, Donghyun Oh et al.
NEURIPS 2025posterarXiv:2505.16705
2
citations
Bayesian Concept Bottleneck Models with LLM Priors
Jean Feng, Avni Kothari, Lucas Zier et al.
NEURIPS 2025posterarXiv:2410.15555
10
citations
Causally Reliable Concept Bottleneck Models
Giovanni De Felice, Arianna Casanova Flores, Francesco De Santis et al.
NEURIPS 2025posterarXiv:2503.04363
5
citations
Disentangled Concepts Speak Louder Than Words: Explainable Video Action Recognition
Jongseo Lee, Wooil Lee, Gyeong-Moon Park et al.
NEURIPS 2025spotlightarXiv:2511.03725
Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions
Hidde Fokkema, Tim van Erven, Sara Magliacane
NEURIPS 2025posterarXiv:2502.06536
3
citations
Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits
Weixin Chen, Han Zhao
NEURIPS 2025posterarXiv:2509.20549