"concept bottleneck models" Papers
14 papers found
Conference
An Analysis of Concept Bottleneck Models: Measuring, Understanding, and Mitigating the Impact of Noisy Annotations
Seonghwan Park, Jueun Mun, Donghyun Oh et al.
NEURIPS 2025arXiv:2505.16705
2
citations
Bayesian Concept Bottleneck Models with LLM Priors
Jean Feng, Avni Kothari, Lucas Zier et al.
NEURIPS 2025arXiv:2410.15555
10
citations
Causally Reliable Concept Bottleneck Models
Giovanni De Felice, Arianna Casanova Flores, Francesco De Santis et al.
NEURIPS 2025arXiv:2503.04363
8
citations
Concept Bottleneck Language Models For Protein Design
Aya Ismail, Tuomas Oikarinen, Amy Wang et al.
ICLR 2025arXiv:2411.06090
16
citations
Concept Bottleneck Large Language Models
Chung-En Sun, Tuomas Oikarinen, Berk Ustun et al.
ICLR 2025arXiv:2412.07992
26
citations
CONDA: Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts
Jihye Choi, Jayaram Raghuram, Yixuan Li et al.
ICLR 2025
Disentangled Concepts Speak Louder Than Words: Explainable Video Action Recognition
Jongseo Lee, Wooil Lee, Gyeong-Moon Park et al.
NEURIPS 2025spotlightarXiv:2511.03725
LICORICE: Label-Efficient Concept-Based Interpretable Reinforcement Learning
Zhuorui Ye, Stephanie Milani, Geoff Gordon et al.
ICLR 2025arXiv:2407.15786
5
citations
Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions
Hidde Fokkema, Tim van Erven, Sara Magliacane
NEURIPS 2025arXiv:2502.06536
3
citations
Show and Tell: Visually Explainable Deep Neural Nets via Spatially-Aware Concept Bottleneck Models
Itay Benou, Tammy Riklin Raviv
CVPR 2025highlightarXiv:2502.20134
6
citations
Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits
Weixin Chen, Han Zhao
NEURIPS 2025arXiv:2509.20549
V2C-CBM: Building Concept Bottlenecks with Vision-to-Concept Tokenizer
Hangzhou He, Lei Zhu, Xinliang Zhang et al.
AAAI 2025paperarXiv:2501.04975
10
citations
Constructing Concept-based Models to Mitigate Spurious Correlations with Minimal Human Effort
Jeeyung Kim, Ze Wang, Qiang Qiu
ECCV 2024arXiv:2407.08947
6
citations
Learning to Intervene on Concept Bottlenecks
David Steinmann, Wolfgang Stammer, Felix Friedrich et al.
ICML 2024arXiv:2308.13453
28
citations