RISE: Randomized Input Sampling for Explanation of Black-box Models

19 June 2018

Abir Das

Papers citing "RISE: Randomized Input Sampling for Explanation of Black-box Models"

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Title
Explainability of Vision Transformers: A Comprehensive Review and New Perspectives Rojina Kashefi Leili Barekatain Mohammad Sabokrou Fatemeh Aghaeipoor ViT 37 9 0 12 Nov 2023
SCAAT: Improving Neural Network Interpretability via Saliency Constrained Adaptive Adversarial Training Rui Xu Wenkang Qin Peixiang Huang Hao Wang Lin Luo FAtt AAML 28 2 0 09 Nov 2023
Zero-shot Translation of Attention Patterns in VQA Models to Natural Language Leonard Salewski A. Sophia Koepke Hendrik P. A. Lensch Zeynep Akata 31 2 0 08 Nov 2023
Explainable AI for Earth Observation: Current Methods, Open Challenges, and Opportunities G. Taşkın E. Aptoula Alp Ertürk 29 2 0 08 Nov 2023
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis Dipanjyoti Paul A. Chowdhury Xinqi Xiong Feng-Ju Chang David Carlyn ... Daniel Rubenstein Charles V. Stewart Tanya Berger-Wolf Yu-Chuan Su Wei-Lun Chao ViT 15 16 0 07 Nov 2023
From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion Models Zhuoshi Pan Yuguang Yao Gaowen Liu Bingquan Shen H. V. Zhao Ramana Rao Kompella Sijia Liu DiffM AAML 25 2 0 04 Nov 2023
Assessing Fidelity in XAI post-hoc techniques: A Comparative Study with Ground Truth Explanations Datasets Miquel Miró-Nicolau Antoni Jaume-i-Capó Gabriel Moyà Alcover XAI 35 11 0 03 Nov 2023
Fast Shapley Value Estimation: A Unified Approach Borui Zhang Baotong Tian Wenzhao Zheng Jie Zhou Jiwen Lu TDI FAtt 19 0 0 02 Nov 2023
MENTOR: Human Perception-Guided Pretraining for Increased Generalization Colton R. Crum Adam Czajka 53 1 0 30 Oct 2023
Visual Explanations via Iterated Integrated Attributions Oren Barkan Yehonatan Elisha Yuval Asher Amit Eshel Noam Koenigstein FAtt XAI 28 18 0 28 Oct 2023
"Honey, Tell Me What's Wrong", Global Explanation of Textual Discriminative Models through Cooperative Generation Antoine Chaffin Julien Delaunay 13 0 0 27 Oct 2023
Understanding Parameter Saliency via Extreme Value Theory Shuo Wang Issei Sato AAML FAtt 19 0 0 27 Oct 2023
Learning to Explain: A Model-Agnostic Framework for Explaining Black Box Models Oren Barkan Yuval Asher Amit Eshel Yehonatan Elisha Noam Koenigstein 35 5 0 25 Oct 2023
On the stability, correctness and plausibility of visual explanation methods based on feature importance Romain Xu-Darme Jenny Benois-Pineau R. Giot Georges Quénot Zakaria Chihani M. Rousset Alexey Zhukov XAI FAtt 20 1 0 25 Oct 2023
Sanity checks for patch visualisation in prototype-based image classification Romain Xu-Darme Georges Quénot Zakaria Chihani M. Rousset 17 6 0 25 Oct 2023
Instance-wise Linearization of Neural Network for Model Interpretation Zhimin Li Shusen Liu B. Kailkhura Timo Bremer Valerio Pascucci MILM FAtt 13 0 0 25 Oct 2023
On the Foundations of Shortcut Learning Katherine Hermann Hossein Mobahi Thomas Fel M. C. Mozer VLM 30 26 0 24 Oct 2023
Deep Integrated Explanations Oren Barkan Yehonatan Elisha Jonathan Weill Yuval Asher Amit Eshel Noam Koenigstein FAtt 41 7 0 23 Oct 2023
Explanation-based Training with Differentiable Insertion/Deletion Metric-aware Regularizers Yuya Yoshikawa Tomoharu Iwata 19 0 0 19 Oct 2023
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation Chongyu Fan Jiancheng Liu Yihua Zhang Eric Wong Dennis Wei Sijia Liu MU 27 123 0 19 Oct 2023
LICO: Explainable Models with Language-Image Consistency Yiming Lei Zilong Li Yangyang Li Junping Zhang Hongming Shan VLM FAtt 17 7 0 15 Oct 2023
Learning Transferable Conceptual Prototypes for Interpretable Unsupervised Domain Adaptation Junyu Gao Xinhong Ma Changsheng Xu 31 4 0 12 Oct 2023
SPADE: Sparsity-Guided Debugging for Deep Neural Networks Arshia Soltani Moakhar Eugenia Iofinova Elias Frantar Dan Alistarh 32 1 0 06 Oct 2023
ViT-ReciproCAM: Gradient and Attention-Free Visual Explanations for Vision Transformer Seokhyun Byun Won-Jo Lee FAtt 18 4 0 04 Oct 2023
SMOOT: Saliency Guided Mask Optimized Online Training Ali Karkehabadi Houman Homayoun Avesta Sasan AAML 19 17 0 01 Oct 2023
Counterfactual Image Generation for adversarially robust and interpretable Classifiers Rafael Bischof F. Scheidegger Michael A. Kraus A. Malossi AAML 30 2 0 01 Oct 2023
Augment to Interpret: Unsupervised and Inherently Interpretable Graph Embeddings Gregory Scafarto Madalina Ciortan Simon Tihon Quentin Ferre 13 2 0 28 Sep 2023
GInX-Eval: Towards In-Distribution Evaluation of Graph Neural Network Explanations Kenza Amara Mennatallah El-Assady Rex Ying 30 6 0 28 Sep 2023
Why do Angular Margin Losses work well for Semi-Supervised Anomalous Sound Detection? Kevin Wilkinghoff Frank Kurth AAML UQCV 25 8 0 27 Sep 2023
Explaining Deep Face Algorithms through Visualization: A Survey Thrupthi Ann S. M. I. C. V. Balasubramanian M. Jawahar CVBM 32 1 0 26 Sep 2023
Multiple Different Black Box Explanations for Image Classifiers Hana Chockler D. A. Kelly Daniel Kroening FAtt 19 0 0 25 Sep 2023
Overview of Class Activation Maps for Visualization Explainability Anh Pham Thi Minh HAI FAtt 31 5 0 25 Sep 2023
Understanding Calibration of Deep Neural Networks for Medical Image Classification A. Sambyal Usma Niyaz N. C. Krishnan Deepti R. Bathula 11 7 0 22 Sep 2023
A matter of attitude: Focusing on positive and active gradients to boost saliency maps Oscar Llorente Jaime Boal Eugenio F. Sánchez-Úbeda FAtt 13 0 0 22 Sep 2023
Can We Reliably Improve the Robustness to Image Acquisition of Remote Sensing of PV Systems? Gabriel Kasmi L. Dubus Yves-Marie Saint Drenan Philippe Blanc 13 3 0 21 Sep 2023
A Hierarchical Neural Framework for Classification and its Explanation in Large Unstructured Legal Documents Nishchal Prasad M. Boughanem Taoufik Dkaki ELM AILaw 26 0 0 19 Sep 2023
On Model Explanations with Transferable Neural Pathways Xinmiao Lin Wentao Bao Qi Yu Yu Kong 12 0 0 18 Sep 2023
Text-to-Image Models for Counterfactual Explanations: a Black-Box Approach Guillaume Jeanneret Loïc Simon Frédéric Jurie DiffM 30 12 0 14 Sep 2023
Interpretability-Aware Vision Transformer Yao Qiang Chengyin Li Prashant Khanduri D. Zhu ViT 82 7 0 14 Sep 2023
FIND: A Function Description Benchmark for Evaluating Interpretability Methods Sarah Schwettmann Tamar Rott Shaham Joanna Materzyñska Neil Chowdhury Shuang Li Jacob Andreas David Bau Antonio Torralba 18 19 0 07 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
Leveraging Reward Consistency for Interpretable Feature Discovery in Reinforcement Learning Qisen Yang Huanqian Wang Mukun Tong Wenjie Shi Gao Huang Shiji Song 27 5 0 04 Sep 2023
Goodhart's Law Applies to NLP's Explanation Benchmarks Jennifer Hsia Danish Pruthi Aarti Singh Zachary Chase Lipton 30 6 0 28 Aug 2023
On Gradient-like Explanation under a Black-box Setting: When Black-box Explanations Become as Good as White-box Yingcheng Cai Gerhard Wunder FAtt 21 0 0 18 Aug 2023
A Dual-Perspective Approach to Evaluating Feature Attribution Methods Yawei Li Yanglin Zhang Kenji Kawaguchi Ashkan Khakzar Bernd Bischl Mina Rezaei FAtt XAI 39 0 0 17 Aug 2023
BSED: Baseline Shapley-Based Explainable Detector Michihiro Kuroki T. Yamasaki FAtt AAML 17 4 0 14 Aug 2023
DCNFIS: Deep Convolutional Neuro-Fuzzy Inference System Mojtaba Yeganejou Kimia Honari Ryan Kluzinski S. Dick M. Lipsett James Miller FedML AI4CE 23 0 0 11 Aug 2023
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods Robin Hesse Simone Schaub-Meyer Stefan Roth AAML 34 32 0 11 Aug 2023
Explainable AI applications in the Medical Domain: a systematic review Nicoletta Prentzas A. Kakas Constantinos S. Pattichis 16 11 0 10 Aug 2023