B-cos Networks: Alignment is All We Need for Interpretability

20 May 2022

Mario Fritz

Bernt Schiele

Papers citing "B-cos Networks: Alignment is All We Need for Interpretability"

50 / 62 papers shown

Title
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection Moritz Vandenhirtz Julia E. Vogt 35 0 0 19 May 2025
Towards Spatially-Aware and Optimally Faithful Concept-Based Explanations Shubham Kumar Dwip Dalal Narendra Ahuja 21 0 0 15 Apr 2025
VITAL: More Understandable Feature Visualization through Distribution Alignment and Relevant Information Flow Ada Gorgun Bernt Schiele Jonas Fischer 34 0 0 28 Mar 2025
Beyond Accuracy: What Matters in Designing Well-Behaved Models? Robin Hesse Doğukan Bağcı Bernt Schiele Simone Schaub-Meyer Stefan Roth VLM 57 0 0 21 Mar 2025
Not Only Text: Exploring Compositionality of Visual Representations in Vision-Language Models Davide Berasi Matteo Farina Massimiliano Mancini Elisa Ricci Nicola Strisciuglio CoGe 66 0 0 21 Mar 2025
Escaping Plato's Cave: Robust Conceptual Reasoning through Interpretable 3D Neural Object Volumes Nhi Pham Bernt Schiele Adam Kortylewski Jonas Fischer 56 0 0 17 Mar 2025
Now you see me! A framework for obtaining class-relevant saliency maps Nils Philipp Walter Jilles Vreeken Jonas Fischer FAtt 40 0 0 10 Mar 2025
Rashomon Sets for Prototypical-Part Networks: Editing Interpretable Models in Real-Time J. Donnelly Zhicheng Guo A. Barnett Hayden McTavish Chaofan Chen Cynthia Rudin 61 0 0 03 Mar 2025
Invariance Pair-Guided Learning: Enhancing Robustness in Neural Networks Martin Surner Abdelmajid Khelil Ludwig Bothmann OOD 51 0 0 26 Feb 2025
Disentangling Visual Transformers: Patch-level Interpretability for Image Classification Guillaume Jeanneret Loïc Simon F. Jurie ViT 44 0 0 24 Feb 2025
B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable Shreyash Arya Sukrut Rao Moritz Bohle Bernt Schiele 68 2 0 28 Jan 2025
COMIX: Compositional Explanations using Prototypes S. Sivaprasad D. Kangin Plamen Angelov Mario Fritz 130 0 0 10 Jan 2025
Label-free Concept Based Multiple Instance Learning for Gigapixel Histopathology Susu Sun Leslie Tessier Frédérique Meeuwsen Clément Grisi Dominique van Midden G. Litjens Christian F. Baumgartner 24 2 0 06 Jan 2025
LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model Xi Wang H. Li Heng Fang Yichen Peng H. Xie Xi Yang Chuntao Li DiffM 72 0 0 16 Dec 2024
OMENN: One Matrix to Explain Neural Networks Adam Wróbel Mikołaj Janusz Bartosz Zieliñski Dawid Rymarczyk FAtt AAML 75 0 0 03 Dec 2024
Unlearning-based Neural Interpretations Ching Lam Choi Alexandre Duplessis Serge Belongie FAtt 42 0 0 10 Oct 2024
InfoDisent: Explainability of Image Classification Models by Information Disentanglement Łukasz Struski Dawid Rymarczyk Jacek Tabor 51 0 0 16 Sep 2024
Revisiting FunnyBirds evaluation framework for prototypical parts networks Szymon Opłatek Dawid Rymarczyk Bartosz Zieliñski 28 3 0 21 Aug 2024
Comprehensive Attribution: Inherently Explainable Vision Model with Feature Detector Xianren Zhang Dongwon Lee Suhang Wang VLM FAtt 40 3 0 27 Jul 2024
Benchmarking the Attribution Quality of Vision Models Robin Hesse Simone Schaub-Meyer Stefan Roth FAtt 29 3 0 16 Jul 2024
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models Jayneel Parekh Quentin Bouniot Pavlo Mozharovskyi A. Newson Florence dÁlché-Buc SSL 55 1 0 01 Jul 2024
Conceptual Learning via Embedding Approximations for Reinforcing Interpretability and Transparency Maor Dikter Tsachi Blau Chaim Baskin 41 0 0 13 Jun 2024
How Video Meetings Change Your Expression Sumit Sarin Utkarsh Mall Purva Tendulkar Carl Vondrick CVBM 32 0 0 03 Jun 2024
Can Implicit Bias Imply Adversarial Robustness? Hancheng Min René Vidal 34 3 0 24 May 2024
LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision Mateusz Pach Dawid Rymarczyk K. Lewandowska Jacek Tabor Bartosz Zieliñski 32 7 0 23 May 2024
IMAFD: An Interpretable Multi-stage Approach to Flood Detection from time series Multispectral Data Ziyang Zhang Plamen Angelov D. Kangin Nicolas Longépé AI4CE 36 1 0 13 May 2024
Enhanced Online Test-time Adaptation with Feature-Weight Cosine Alignment Weiqin Chuah Ruwan Tennakoon A. Bab-Hadiashar 21 1 0 12 May 2024
Visual Concept Connectome (VCC): Open World Concept Discovery and their Interlayer Connections in Deep Models M. Kowal Richard P. Wildes Konstantinos G. Derpanis GNN 30 8 0 02 Apr 2024
Towards Explaining Hypercomplex Neural Networks Eleonora Lopez Eleonora Grassucci D. Capriotti Danilo Comminiello 38 3 0 26 Mar 2024
What Sketch Explainability Really Means for Downstream Tasks Hmrishav Bandyopadhyay Pinaki Nath Chowdhury A. Bhunia Aneeshan Sain Tao Xiang Yi-Zhe Song 30 4 0 14 Mar 2024
Unsupervised Domain Adaptation within Deep Foundation Latent Spaces D. Kangin Plamen Angelov 16 1 0 22 Feb 2024
Good Teachers Explain: Explanation-Enhanced Knowledge Distillation Amin Parchami-Araghi Moritz Bohle Sukrut Rao Bernt Schiele FAtt 8 3 0 05 Feb 2024
InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts Vinitra Swamy Syrielle Montariol Julian Blackwell Jibril Frej Martin Jaggi Tanja Kaser 31 3 0 05 Feb 2024
B-Cos Aligned Transformers Learn Human-Interpretable Features Manuel Tran Amal Lahiani Yashin Dicente Cid Melanie Boxberg Peter Lienemann C. Matek S. J. Wagner Fabian J. Theis Eldad Klaiman Tingying Peng MedIm ViT 13 2 0 16 Jan 2024
Q-SENN: Quantized Self-Explaining Neural Networks Thomas Norrenbrock Marco Rudolph Bodo Rosenhahn FAtt AAML MILM 23 6 0 21 Dec 2023
Mixture of Gaussian-distributed Prototypes with Generative Modelling for Interpretable and Trustworthy Image Recognition Chong Wang Yuanhong Chen Fengbei Liu Yuyuan Liu Davis J. McCarthy Helen Frazer Gustavo Carneiro 18 1 0 30 Nov 2023
Towards interpretable-by-design deep learning algorithms Plamen Angelov D. Kangin Ziyang Zhang 16 6 0 19 Nov 2023
Greedy PIG: Adaptive Integrated Gradients Kyriakos Axiotis Sami Abu-El-Haija Lin Chen Matthew Fahrbach Gang Fu FAtt 26 0 0 10 Nov 2023
Frozen Transformers in Language Models Are Effective Visual Encoder Layers Ziqi Pang Ziyang Xie Yunze Man Yu-xiong Wang 45 25 0 19 Oct 2023
Latent Diffusion Counterfactual Explanations Karim Farid Simon Schrodi Max Argus Thomas Brox DiffM 33 12 0 10 Oct 2023
Don't Miss Out on Novelty: Importance of Novel Features for Deep Anomaly Detection S. Sivaprasad Mario Fritz AAML 18 0 0 01 Oct 2023
From Classification to Segmentation with Explainable AI: A Study on Crack Detection and Growth Monitoring Florent Forest Hugo Porta D. Tuia Olga Fink 19 7 0 20 Sep 2023
Text-to-Image Models for Counterfactual Explanations: a Black-Box Approach Guillaume Jeanneret Loïc Simon Frédéric Jurie DiffM 28 12 0 14 Sep 2023
Interpretability-Aware Vision Transformer Yao Qiang Chengyin Li Prashant Khanduri D. Zhu ViT 80 7 0 14 Sep 2023
PDiscoNet: Semantically consistent part discovery for fine-grained recognition Robert van der Klis Stephan Alaniz Massimiliano Mancini C. Dantas Dino Ienco Zeynep Akata Diego Marcos 17 11 0 06 Sep 2023
DeViL: Decoding Vision features into Language Meghal Dani Isabel Rio-Torto Stephan Alaniz Zeynep Akata VLM 40 7 0 04 Sep 2023
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods Robin Hesse Simone Schaub-Meyer Stefan Roth AAML 32 32 0 11 Aug 2023
Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability Usha Bhalla Suraj Srinivas Himabindu Lakkaraju FAtt CML 26 6 0 27 Jul 2023
What's meant by explainable model: A Scoping Review Mallika Mainali Rosina O. Weber XAI 29 0 0 18 Jul 2023
Single Domain Generalization via Normalised Cross-correlation Based Convolutions Weiqin Chuah Ruwan Tennakoon R. Hoseinnezhad David Suter A. Bab-Hadiashar OOD 17 3 0 12 Jul 2023