Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations

16 August 2023

Papers citing "Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations"

28 / 28 papers shown

Title
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts Mikolaj Sacha Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski VLM 61 29 0 28 Jan 2023
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction Dawid Rymarczyk D. Dobrowolski Tomasz Danel 93 4 0 07 Oct 2022
This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation Srishti Gautam Marina M.-C. Höhne Stine Hansen Robert Jenssen Michael C. Kampffmeyer 57 49 0 27 Aug 2021
This Looks Like That... Does it? Shortcomings of Latent Space Prototype Interpretability in Deep Networks Adrian Hoffmann Claudio Fanconi Rahul Rade Jonas Köhler 54 63 0 05 May 2021
Visual Saliency Transformer Nian Liu Ni Zhang Kaiyuan Wan Ling Shao Junwei Han ViT 297 359 0 25 Apr 2021
IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography A. Barnett F. Schwartz Chaofan Tao Chaofan Chen Yinhao Ren J. Lo Cynthia Rudin 75 140 0 23 Mar 2021
XProtoNet: Diagnosis in Chest Radiography with Global and Local Explanations Eunji Kim Siwon Kim Minji Seo Sungroh Yoon ViT FAtt 71 115 0 19 Mar 2021
Attribute Prototype Network for Zero-Shot Learning Wenjia Xu Yongqin Xian Jiuniu Wang Bernt Schiele Zeynep Akata 55 293 0 19 Aug 2020
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction Esther Puyol-Antón Chong Chen J. Clough B. Ruijsink B. Sidhu ... M. Elliott Vishal S. Mehta Daniel Rueckert C. Rinaldi A. King 54 32 0 24 Jun 2020
Counterfactual VQA: A Cause-Effect Look at Language Bias Yulei Niu Kaihua Tang Hanwang Zhang Zhiwu Lu Xiansheng Hua Ji-Rong Wen CML 117 401 0 08 Jun 2020
There and Back Again: Revisiting Backpropagation Saliency Methods Sylvestre-Alvise Rebuffi Ruth C. Fong Xu Ji Andrea Vedaldi FAtt XAI 68 113 0 06 Apr 2020
Concept Whitening for Interpretable Image Recognition Zhi Chen Yijie Bei Cynthia Rudin FAtt 78 322 0 05 Feb 2020
Understanding Deep Networks via Extremal Perturbations and Smooth Masks Ruth C. Fong Mandela Patrick Andrea Vedaldi AAML 73 416 0 18 Oct 2019
Interpretable Image Recognition with Hierarchical Prototypes Peter Hase Chaofan Chen Oscar Li Cynthia Rudin VLM 83 111 0 25 Jun 2019
Interpreting Adversarially Trained Convolutional Neural Networks Tianyuan Zhang Zhanxing Zhu AAML GAN FAtt 102 161 0 23 May 2019
On the Connection Between Adversarial Robustness and Saliency Map Interpretability Christian Etmann Sebastian Lunz Peter Maass Carola-Bibiane Schönlieb AAML FAtt 58 162 0 10 May 2019
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet Wieland Brendel Matthias Bethge SSL FAtt 96 561 0 20 Mar 2019
Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition Heliang Zheng Jianlong Fu Zhengjun Zha Jiebo Luo 92 384 0 14 Mar 2019
Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded Ramprasaath R. Selvaraju Stefan Lee Yilin Shen Hongxia Jin Shalini Ghosh Larry Heck Dhruv Batra Devi Parikh FAtt VLM 64 254 0 11 Feb 2019
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 141 1,967 0 08 Oct 2018
This Looks Like That: Deep Learning for Interpretable Image Recognition Chaofan Chen Oscar Li Chaofan Tao A. Barnett Jonathan Su Cynthia Rudin 243 1,186 0 27 Jun 2018
Towards Robust Interpretability with Self-Explaining Neural Networks David Alvarez-Melis Tommi Jaakkola MILM XAI 126 946 0 20 Jun 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 104 1,783 0 30 May 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 219 1,842 0 30 Nov 2017
Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions Oscar Li Hao Liu Chaofan Chen Cynthia Rudin 176 591 0 13 Oct 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 16,990 0 16 Feb 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 280 19,066 0 20 Dec 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 312 7,308 0 20 Dec 2013