Label-Free Concept Bottleneck Models

12 April 2023

Papers citing "Label-Free Concept Bottleneck Models"

24 / 124 papers shown

Title
Estimation of Concept Explanations Should be Uncertainty Aware Vihari Piratla Juyeon Heo Katherine M. Collins Sukriti Singh Adrian Weller 24 1 0 13 Dec 2023
CLIP-QDA: An Explainable Concept Bottleneck Model Rémi Kazmierczak Eloise Berthier Goran Frehse Gianni Franchi 19 7 0 30 Nov 2023
Towards Concept-based Interpretability of Skin Lesion Diagnosis using Vision-Language Models Cristiano Patrício Luís F. Teixeira João C. Neves 13 6 0 24 Nov 2023
Auxiliary Losses for Learning Generalizable Concept-based Models Ivaxi Sheth Samira Ebrahimi Kahou 32 24 0 18 Nov 2023
Driving through the Concept Gridlock: Unraveling Explainability Bottlenecks in Automated Driving J. Echterhoff An Yan Kyungtae Han Amr Abdelraouf Rohit Gupta Julian McAuley 24 7 0 25 Oct 2023
From Neural Activations to Concepts: A Survey on Explaining Concepts in Neural Networks Jae Hee Lee Sergio Lanza Stefan Wermter 24 8 0 18 Oct 2023
Transparent Anomaly Detection via Concept-based Explanations Laya Rafiee Sevyeri Ivaxi Sheth Farhood Farahnak Samira Ebrahimi Kahou S. Enger 27 4 0 16 Oct 2023
SurroCBM: Concept Bottleneck Surrogate Models for Generative Post-hoc Explanation Bo Pan Zhenke Liu Yifei Zhang Liang Zhao 38 2 0 11 Oct 2023
DISCOVER: Making Vision Networks Interpretable via Competition and Dissection Konstantinos P. Panousis S. Chatzis 30 5 0 07 Oct 2023
Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models An Yan Yu-Xiang Wang Yiwu Zhong Zexue He Petros Karypis ... Chengyu Dong Amilcare Gentili Chun-Nan Hsu Jingbo Shang Julian McAuley 27 30 0 04 Oct 2023
Coarse-to-Fine Concept Bottleneck Models Konstantinos P. Panousis Dino Ienco Diego Marcos 28 5 0 03 Oct 2023
Learning to Receive Help: Intervention-Aware Concept Embedding Models M. Zarlenga Katherine M. Collins Krishnamurthy Dvijotham Adrian Weller Z. Shams M. Jamnik 24 23 0 29 Sep 2023
Interpretability is in the Mind of the Beholder: A Causal Framework for Human-interpretable Representation Learning Emanuele Marconato Andrea Passerini Stefano Teso 36 13 0 14 Sep 2023
Automatic Concept Embedding Model (ACEM): No train-time concepts, No issue! Rishabh Jain LRM 32 0 0 07 Sep 2023
Learning to Intervene on Concept Bottlenecks David Steinmann Wolfgang Stammer Felix Friedrich Kristian Kersting 17 19 0 25 Aug 2023
Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions Kwan Ho Ryan Chan Aditya Chattopadhyay B. Haeffele René Vidal 40 0 0 24 Aug 2023
Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification In-Ho Kim Jongha Kim Joon-Young Choi Hyunwoo J. Kim 26 13 0 23 Aug 2023
Sparse Linear Concept Discovery Models Konstantinos P. Panousis Dino Ienco Diego Marcos 34 15 0 21 Aug 2023
Concept-Monitor: Understanding DNN training through individual neurons Mohammad Ali Khan Tuomas P. Oikarinen Tsui-Wei Weng 21 2 0 26 Apr 2023
Human Uncertainty in Concept-Based AI Systems Katherine M. Collins Matthew Barker M. Zarlenga Naveen Raman Umang Bhatt M. Jamnik Ilia Sucholutsky Adrian Weller Krishnamurthy Dvijotham 66 39 0 22 Mar 2023
Hierarchical Explanations for Video Action Recognition Sadaf Gulshad Teng Long Nanne van Noord FAtt 26 6 0 01 Jan 2023
Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off M. Zarlenga Pietro Barbiero Gabriele Ciravegna G. Marra Francesco Giannini ... F. Precioso S. Melacci Adrian Weller Pietro Lio' M. Jamnik 79 52 0 19 Sep 2022
Post-hoc Concept Bottleneck Models Mert Yuksekgonul Maggie Wang James Zou 145 185 0 31 May 2022
Medical Visual Question Answering: A Survey Zhihong Lin Donghao Zhang Qingyi Tao Danli Shi Gholamreza Haffari Qi Wu M. He Z. Ge 28 111 0 19 Nov 2021