Concept Whitening for Interpretable Image Recognition

5 February 2020

Zhi Chen

Papers citing "Concept Whitening for Interpretable Image Recognition"

22 / 22 papers shown

Title
If Concept Bottlenecks are the Question, are Foundation Models the Answer? Nicola Debole Pietro Barbiero Francesco Giannini Andrea Passerini Stefano Teso Emanuele Marconato 44 0 0 28 Apr 2025
Is What You Ask For What You Get? Investigating Concept Associations in Text-to-Image Models Salma Abdel Magid Weiwei Pan Simon Warchol Grace Guo Junsik Kim Mahia Rahman Hanspeter Pfister 84 0 0 06 Oct 2024
CEIR: Concept-based Explainable Image Representation Learning Yan Cui Shuhong Liu Liuzhuozheng Li Zhiyuan Yuan SSL VLM 10 3 0 17 Dec 2023
Interpretability-Aware Vision Transformer Yao Qiang Chengyin Li Prashant Khanduri D. Zhu ViT 74 7 0 14 Sep 2023
LR-XFL: Logical Reasoning-based Explainable Federated Learning Yanci Zhang Hanyou Yu LRM 8 7 0 24 Aug 2023
Exploring XAI for the Arts: Explaining Latent Space in Generative Music Nick Bryan-Kinns Berker Banar Corey Ford Courtney N. Reed Yixiao Zhang S. Colton Jack Armitage 9 30 0 10 Aug 2023
Uncovering Unique Concept Vectors through Latent Space Decomposition Mara Graziani Laura Mahony An-phi Nguyen Henning Muller Vincent Andrearczyk 23 4 0 13 Jul 2023
Coherent Concept-based Explanations in Medical Image and Its Application to Skin Lesion Diagnosis Cristiano Patrício João C. Neves Luís F. Teixeira MedIm FAtt 19 16 0 10 Apr 2023
ICICLE: Interpretable Class Incremental Continual Learning Dawid Rymarczyk Joost van de Weijer Bartosz Zieliñski Bartlomiej Twardowski CLL 10 28 0 14 Mar 2023
Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint Borui Zhang Wenzhao Zheng Jie Zhou Jiwen Lu AAML 20 7 0 18 Dec 2022
Joint localization and classification of breast tumors on ultrasound images using a novel auxiliary attention-based framework Zong Fan Ping Gong Shanshan Tang Christine U. Lee Xiaohui Zhang P. Song Shigao Chen Hua Li 8 2 0 11 Oct 2022
TCNL: Transparent and Controllable Network Learning Via Embedding Human-Guided Concepts Zhihao Wang Chuang Zhu 14 1 0 07 Oct 2022
Causality-Inspired Taxonomy for Explainable Artificial Intelligence Pedro C. Neto Tiago B. Gonccalves João Ribeiro Pinto W. Silva Ana F. Sequeira Arun Ross Jaime S. Cardoso XAI 20 12 0 19 Aug 2022
When are Post-hoc Conceptual Explanations Identifiable? Tobias Leemann Michael Kirchhof Yao Rong Enkelejda Kasneci Gjergji Kasneci 50 10 0 28 Jun 2022
From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation Reduan Achtibat Maximilian Dreyer Ilona Eisenbraun S. Bosse Thomas Wiegand Wojciech Samek Sebastian Lapuschkin FAtt 20 131 0 07 Jun 2022
Post-hoc Concept Bottleneck Models Mert Yuksekgonul Maggie Wang James Y. Zou 130 182 0 31 May 2022
Learnable Visual Words for Interpretable Image Recognition Wenxi Xiao Zhengming Ding Hongfu Liu VLM 8 2 0 22 May 2022
ConceptExplainer: Interactive Explanation for Deep Neural Networks from a Concept Perspective Jinbin Huang Aditi Mishra Bum Chul Kwon Chris Bryan FAtt HAI 17 30 0 04 Apr 2022
From Concept Drift to Model Degradation: An Overview on Performance-Aware Drift Detectors Firas Bayram Bestoun S. Ahmed A. Kassler 15 206 0 21 Mar 2022
Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence Frederik Pahde Maximilian Dreyer Leander Weber Moritz Weckbecker Christopher J. Anders Thomas Wiegand Wojciech Samek Sebastian Lapuschkin 55 7 0 07 Feb 2022
Editing a classifier by rewriting its prediction rules Shibani Santurkar Dimitris Tsipras Mahalaxmi Elango David Bau Antonio Torralba A. Madry KELM 158 89 0 02 Dec 2021
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan Ö. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 117 293 0 17 Oct 2019