Relevance-driven Input Dropout: an Explanation-guided Regularization Technique

27 May 2025

Papers citing "Relevance-driven Input Dropout: an Explanation-guided Regularization Technique"

50 / 59 papers shown

Title
Mechanistic understanding and validation of large AI models with SemanticLens Maximilian Dreyer J. Berend Tobias Labarta Johanna Vielhaben Thomas Wiegand Sebastian Lapuschkin Wojciech Samek 48 3 0 10 Jan 2025
Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers Sayed Mohammad Vakilzadeh Hatefi Maximilian Dreyer Reduan Achtibat Thomas Wiegand Wojciech Samek Sebastian Lapuschkin ViT 45 2 0 22 Aug 2024
The Missing Curve Detectors of InceptionV1: Applying Sparse Autoencoders to InceptionV1 Early Vision Liv Gorton 31 16 0 06 Jun 2024
Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE) Usha Bhalla Alexander X. Oesterling Suraj Srinivas Flavio du Pin Calmon Himabindu Lakkaraju 71 38 0 16 Feb 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 47 31 0 08 Feb 2024
Understanding Video Transformers via Universal Concept Discovery M. Kowal Achal Dave Rares Andrei Ambrus Adrien Gaidon Konstantinos G. Derpanis P. Tokmakov ViT 72 9 0 19 Jan 2024
Sparse Autoencoders Find Highly Interpretable Features in Language Models Hoagy Cunningham Aidan Ewart Logan Riggs R. Huben Lee Sharkey MILM 64 382 0 15 Sep 2023
Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees Johanna Vielhaben Stefan Blücher Nils Strodthoff 44 39 0 27 Jan 2023
AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning Tao Yang Jinghao Deng Xiaojun Quan Qifan Wang Shaoliang Nie 50 4 0 12 Oct 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 46 138 0 07 Jun 2022
Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI Sami Ede Serop Baghdadlian Leander Weber A. Nguyen Dario Zanca Wojciech Samek Sebastian Lapuschkin CLL 36 7 0 04 May 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 677 12,525 0 04 Mar 2022
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond Anna Hedström Leander Weber Dilyara Bareeva Daniel G. Krakowczyk Franz Motzkus Wojciech Samek Sebastian Lapuschkin Marina M.-C. Höhne XAI ELM 35 173 0 14 Feb 2022
Measurably Stronger Explanation Reliability via Model Canonization Franz Motzkus Leander Weber Sebastian Lapuschkin FAtt 33 7 0 14 Feb 2022
$ECQ$^{\text{x}}$: Explainability-Driven Quantization for Low-Bit and Sparse DNNs$ ECQ $^{\text{x}}$ : Explainability-Driven Quantization for Low-Bit and Sparse DNNs Daniel Becking Maximilian Dreyer Wojciech Samek Karsten Müller Sebastian Lapuschkin MQ 286 14 0 09 Sep 2021
R-Drop: Regularized Dropout for Neural Networks Xiaobo Liang Lijun Wu Juntao Li Yue Wang Qi Meng Tao Qin Wei Chen Hao Fei Tie-Yan Liu 59 430 0 28 Jun 2021
Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy Christopher J. Anders David Neumann Wojciech Samek K. Müller Sebastian Lapuschkin 57 65 0 24 Jun 2021
Large-scale Unsupervised Semantic Segmentation Shangqi Gao Zhong-Yu Li Ming-Hsuan Yang Mingg-Ming Cheng Junwei Han Philip Torr UQCV 80 86 0 06 Jun 2021
Noise Injection-based Regularization for Point Cloud Processing Xiao Zang Yi Xie Siyu Liao Jie Chen Bo Yuan 3DPC 35 2 0 28 Mar 2021
PCT: Point cloud transformer Meng-Hao Guo Junxiong Cai Zheng-Ning Liu Tai-Jiang Mu Ralph Robert Martin Shimin Hu ViT 3DPC 112 1,599 0 17 Dec 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 314 40,217 0 22 Oct 2020
Utilizing Explainable AI for Quantization and Pruning of Deep Neural Networks Muhammad Sabih Frank Hannig J. Teich MQ 59 23 0 20 Aug 2020
Explicit Regularisation in Gaussian Noise Injections A. Camuto M. Willetts Umut Simsekli Stephen J. Roberts Chris Holmes 43 57 0 14 Jul 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization Dan Hendrycks Steven Basart Norman Mu Saurav Kadavath Frank Wang ... Samyak Parajuli Mike Guo D. Song Jacob Steinhardt Justin Gilmer OOD 252 1,715 0 29 Jun 2020
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI L. Arras Ahmed Osman Wojciech Samek XAI AAML 54 153 0 16 Mar 2020
xAI-GAN: Enhancing Generative Adversarial Networks via Explainable AI Systems Vineel Nagisetty Laura Graves Joseph Scott Vijay Ganesh GAN DRL 40 28 0 24 Feb 2020
Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning Seul-Ki Yeom P. Seegerer Sebastian Lapuschkin Alexander Binder Simon Wiedemann K. Müller Wojciech Samek CVBM 35 203 0 18 Dec 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt D. Song OODD 164 1,454 0 16 Jul 2019
When Does Label Smoothing Help? Rafael Müller Simon Kornblith Geoffrey E. Hinton UQCV 125 1,931 0 06 Jun 2019
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned Elena Voita David Talbot F. Moiseev Rico Sennrich Ivan Titov 76 1,120 0 23 May 2019
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features Sangdoo Yun Dongyoon Han Seong Joon Oh Sanghyuk Chun Junsuk Choe Y. Yoo OOD 572 4,735 0 13 May 2019
Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations Fred Hohman Haekyu Park Caleb Robinson Duen Horng Chau FAtt 3DH HAI 37 215 0 04 Apr 2019
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks Jason W. Wei Kai Zou 76 1,931 0 31 Jan 2019
GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks Christopher Bowles Liang Chen Ricardo Guerrero P. Bentley R. Gunn A. Hammers D. A. Dickie M. V. Valdés Hernández Joanna M. Wardlaw Daniel Rueckert GAN MedIm 54 424 0 25 Oct 2018
Dynamic Graph CNN for Learning on Point Clouds Yue Wang Yongbin Sun Ziwei Liu Sanjay E. Sarma M. Bronstein Justin Solomon GNN 3DPC 223 6,076 0 24 Jan 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 158 1,817 0 30 Nov 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 233 9,687 0 25 Oct 2017
Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization Hyeonwoo Noh Tackgeun You Jonghwan Mun Bohyung Han NoLa 58 198 0 14 Oct 2017
Random Erasing Data Augmentation Zhun Zhong Liang Zheng Guoliang Kang Shaozi Li Yi Yang 67 3,614 0 16 Aug 2017
PatchShuffle Regularization Guoliang Kang Xuanyi Dong Liang Zheng Yi Yang 39 75 0 22 Jul 2017
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space C. Qi L. Yi Hao Su Leonidas Guibas 3DPC 3DV 249 11,000 0 07 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 446 21,459 0 22 May 2017
Network Dissection: Quantifying Interpretability of Deep Visual Representations David Bau Bolei Zhou A. Khosla A. Oliva Antonio Torralba MILM FAtt 80 1,503 1 19 Apr 2017
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization Krishna Kumar Singh Yong Jae Lee 64 679 0 13 Apr 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 45 1,514 0 11 Apr 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 119 3,848 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 108 5,920 0 04 Mar 2017
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis L. Zintgraf Taco S. Cohen T. Adel Max Welling FAtt 106 707 0 15 Feb 2017
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas Guibas 3DH 3DPC 3DV PINN 395 14,191 0 02 Dec 2016
DisturbLabel: Regularizing CNN on the Loss Layer Lingxi Xie Jingdong Wang Zhen Wei Meng Wang Qi Tian 61 251 0 30 Apr 2016