Feature Perturbation Augmentation for Reliable Evaluation of Importance
Estimators in Neural Networks

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Feature Perturbation Augmentation for Reliable Evaluation of Importance Estimators in Neural Networks

Pattern Recognition Letters (PR), 2023

2 March 2023

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Papers citing "Feature Perturbation Augmentation for Reliable Evaluation of Importance Estimators in Neural Networks"

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Title
Rethinking Explanation Evaluation under the Retraining Scheme Yi Cai Thibaud Ardoin Mayank Gulati Gerhard Wunder LRM 61 0 0 11 Nov 2025
Explain and Monitor Deep Learning Models for Computer Vision using Obz AI N. C. Chung Jakub Binda VLM 117 1 0 25 Aug 2025
Integrative CAM: Adaptive Layer Fusion for Comprehensive Interpretation of CNNs Aniket K. Singh Debasis Chaudhuri Manish P. Singh Samiran Chattopadhyay 219 4 0 02 Dec 2024
False Sense of Security in Explainable Artificial Intelligence (XAI) N. C. Chung Hongkyou Chung Hearim Lee L. Brocki Hongbeom Chung George C. Dyer 315 4 0 06 May 2024
AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers Reduan Achtibat Sayed Mohammad Vakilzadeh Hatefi Maximilian Dreyer Aakriti Jain Thomas Wiegand Sebastian Lapuschkin Wojciech Samek 295 73 0 08 Feb 2024
Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks Stefan Blücher Johanna Vielhaben Nils Strodthoff AAML 252 30 0 12 Jan 2024
Class-Discriminative Attention Maps for Vision Transformers L. Brocki Jakub Binda N. C. Chung MedIm 289 7 0 04 Dec 2023