This Looks Like That... Does it? Shortcomings of Latent Space Prototype Interpretability in Deep Networks

5 May 2021

Papers citing "This Looks Like That... Does it? Shortcomings of Latent Space Prototype Interpretability in Deep Networks"

49 / 49 papers shown

Title
MERA: Multimodal and Multiscale Self-Explanatory Model with Considerably Reduced Annotation for Lung Nodule Diagnosis Jiahao Lu Chong Yin Silvia Ingala Kenny Erleben M. Nielsen S. Darkner 59 0 0 27 Apr 2025
On Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs Gesina Schwalbe Georgii Mikriukov Edgar Heinert Stavros Gerolymatos Mert Keser Alois Knoll Matthias Rottmann Annika Mütze 69 0 0 11 Apr 2025
Birds look like cars: Adversarial analysis of intrinsically interpretable deep learning Hubert Baniecki P. Biecek AAML 83 0 0 11 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 100 0 0 03 Mar 2025
QPM: Discrete Optimization for Globally Interpretable Image Classification Thomas Norrenbrock Timo Kaiser Sovan Biswas R. Manuvinakurike Bodo Rosenhahn 94 0 0 27 Feb 2025
Tell me why: Visual foundation models as self-explainable classifiers Hugues Turbé Mina Bjelogrlic G. Mengaldo Christian Lovis 97 0 0 26 Feb 2025
A Robust Prototype-Based Network with Interpretable RBF Classifier Foundations S. Saralajew Ashish Rana T. Villmann Ammar Shaker OOD 99 1 0 20 Dec 2024
Strategies and Challenges of Efficient White-Box Training for Human Activity Recognition Daniel Geissler Bo Zhou P. Lukowicz HAI 84 1 0 11 Dec 2024
Prototype-Based Methods in Explainable AI and Emerging Opportunities in the Geosciences Anushka Narayanan Karianne J. Bergen 60 1 0 22 Oct 2024
Fool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support Setting Maxime Kayser Bayar I. Menzat Cornelius Emde Bogdan Bercean Alex Novak Abdala Espinosa B. Papież Susanne Gaube Thomas Lukasiewicz Oana-Maria Camburu 63 3 0 16 Oct 2024
CaBRNet, an open-source library for developing and evaluating Case-Based Reasoning Models Romain Xu-Darme Aymeric Varasse Alban Grastien Julien Girard Zakaria Chihani 35 0 0 25 Sep 2024
Concept-Based Explanations in Computer Vision: Where Are We and Where Could We Go? Jae Hee Lee Georgii Mikriukov Gesina Schwalbe Stefan Wermter D. Wolter 55 2 0 20 Sep 2024
Semantic Prototypes: Enhancing Transparency Without Black Boxes Orfeas Menis Mastromichalakis Giorgos Filandrianos Jason Liartis Edmund Dervakos Giorgos Stamou 56 2 0 18 Jul 2024
This Probably Looks Exactly Like That: An Invertible Prototypical Network Zachariah Carmichael Timothy Redgrave Daniel Gonzalez Cedre Walter J. Scheirer BDL 62 2 0 16 Jul 2024
ProtoS-ViT: Visual foundation models for sparse self-explainable classifications Hugues Turbé Mina Bjelogrlic G. Mengaldo Christian Lovis ViT 44 6 0 14 Jun 2024
Enhancing Interpretability of Vertebrae Fracture Grading using Human-interpretable Prototypes Poulami Sinhamahapatra Suprosanna Shit Anjany Sekuboyina M. Husseini D. Schinz Nicolas Lenhart Bjoern Menze Jan Kirschke Karsten Roscher Stephan Guennemann 76 1 0 03 Apr 2024
On the Concept Trustworthiness in Concept Bottleneck Models Qihan Huang Mingli Song Jingwen Hu Haofei Zhang Yong Wang Mingli Song 55 9 0 21 Mar 2024
ComFe: An Interpretable Head for Vision Transformers Evelyn J. Mannix H. Bondell Howard Bondell VLM ViT 51 1 0 07 Mar 2024
Vision Transformers with Natural Language Semantics Young-Kyung Kim Matías Di Martino Guillermo Sapiro ViT 28 5 0 27 Feb 2024
Q-SENN: Quantized Self-Explaining Neural Networks Thomas Norrenbrock Marco Rudolph Bodo Rosenhahn FAtt AAML MILM 62 6 0 21 Dec 2023
ProtoArgNet: Interpretable Image Classification with Super-Prototypes and Argumentation [Technical Report] Hamed Ayoobi Nico Potyka Francesca Toni 51 3 0 26 Nov 2023
Robust Text Classification: Analyzing Prototype-Based Networks Zhivar Sourati D. Deshpande Filip Ilievski Kiril Gashteovski S. Saralajew OOD OffRL 47 2 0 11 Nov 2023
This Reads Like That: Deep Learning for Interpretable Natural Language Processing Claudio Fanconi Moritz Vandenhirtz Severin Husmann Julia E. Vogt FAtt 19 2 0 25 Oct 2023
Sanity checks for patch visualisation in prototype-based image classification Romain Xu-Darme Georges Quénot Zakaria Chihani M. Rousset 24 6 0 25 Oct 2023
On the Interpretability of Part-Prototype Based Classifiers: A Human Centric Analysis Omid Davoodi Shayan Mohammadizadehsamakosh Majid Komeili 40 11 0 10 Oct 2023
PRIME: Prioritizing Interpretability in Failure Mode Extraction Keivan Rezaei Mehrdad Saberi Mazda Moayeri Soheil Feizi 38 8 0 29 Sep 2023
Pixel-Grounded Prototypical Part Networks Zachariah Carmichael Suhas Lohit A. Cherian Michael Jeffrey Jones Walter J. Scheirer 70 11 0 25 Sep 2023
Interpretability is in the Mind of the Beholder: A Causal Framework for Human-interpretable Representation Learning Emanuele Marconato Andrea Passerini Stefano Teso 41 13 0 14 Sep 2023
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations Mikolaj Sacha Bartosz Jura Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski 37 14 0 16 Aug 2023
The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image Classifiers Meike Nauta Christin Seifert 65 11 0 26 Jul 2023
Take 5: Interpretable Image Classification with a Handful of Features Thomas Norrenbrock Marco Rudolph Bodo Rosenhahn FAtt 52 7 0 23 Mar 2023
ICICLE: Interpretable Class Incremental Continual Learning Dawid Rymarczyk Joost van de Weijer Bartosz Zieliñski Bartlomiej Twardowski CLL 39 28 0 14 Mar 2023
Schema Inference for Interpretable Image Classification Haofei Zhang Mengqi Xue Xiaokang Liu Kaixuan Chen Mingli Song Mingli Song OCL 52 3 0 12 Mar 2023
Sanity checks and improvements for patch visualisation in prototype-based image classification Romain Xu-Darme Georges Quénot Zakaria Chihani M. Rousset 37 3 0 20 Jan 2023
Evaluation and Improvement of Interpretability for Self-Explainable Part-Prototype Networks Qihan Huang Mengqi Xue Wenqi Huang Haofei Zhang Mingli Song Yongcheng Jing Mingli Song AAML 30 27 0 12 Dec 2022
"Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction Sunnie S. Y. Kim E. A. Watkins Olga Russakovsky Ruth C. Fong Andrés Monroy-Hernández 47 109 0 02 Oct 2022
Leveraging Explanations in Interactive Machine Learning: An Overview Stefano Teso Öznur Alkan Wolfgang Stammer Elizabeth M. Daly XAI FAtt LRM 54 62 0 29 Jul 2022
Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks Tilman Raukur A. Ho Stephen Casper Dylan Hadfield-Menell AAML AI4CE 33 126 0 27 Jul 2022
Overlooked factors in concept-based explanations: Dataset choice, concept learnability, and human capability V. V. Ramaswamy Sunnie S. Y. Kim Ruth C. Fong Olga Russakovsky FAtt 37 29 0 20 Jul 2022
Concept-level Debugging of Part-Prototype Networks A. Bontempelli Stefano Teso Katya Tentori Fausto Giunchiglia Andrea Passerini 41 52 0 31 May 2022
GlanceNets: Interpretabile, Leak-proof Concept-based Models Emanuele Marconato Andrea Passerini Stefano Teso 113 64 0 31 May 2022
Explainable Deep Learning Methods in Medical Image Classification: A Survey Cristiano Patrício João C. Neves Luís F. Teixeira XAI 29 54 0 10 May 2022
Complexity from Adaptive-Symmetries Breaking: Global Minima in the Statistical Mechanics of Deep Neural Networks Shaun Li AI4CE 51 0 0 03 Jan 2022
HIVE: Evaluating the Human Interpretability of Visual Explanations Sunnie S. Y. Kim Nicole Meister V. V. Ramaswamy Ruth C. Fong Olga Russakovsky 68 114 0 06 Dec 2021
Interpretable Image Classification with Differentiable Prototypes Assignment Dawid Rymarczyk Lukasz Struski Michal Górszczak K. Lewandowska Jacek Tabor Bartosz Zieliñski 41 98 0 06 Dec 2021
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods Zohaib Salahuddin Henry C. Woodruff A. Chatterjee Philippe Lambin 31 308 0 01 Nov 2021
Toward a Unified Framework for Debugging Concept-based Models A. Bontempelli Fausto Giunchiglia Andrea Passerini Stefano Teso 22 4 0 23 Sep 2021
FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging Karim Lekadira Richard Osuala C. Gallin Noussair Lazrak Kaisar Kushibar ... Nickolas Papanikolaou Zohaib Salahuddin Henry C. Woodruff Philippe Lambin L. Martí-Bonmatí AI4TS 90 59 0 20 Sep 2021
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification Dawid Rymarczyk Adam Pardyl Jaroslaw Kraus Aneta Kaczyńska M. Skomorowski Bartosz Zieliñski 17 22 0 24 Aug 2021