What Do You See? Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural Backdoors

22 September 2020

Papers citing "What Do You See? Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural Backdoors"

33 / 33 papers shown

Title
Evaluating Explanation Quality in X-IDS Using Feature Alignment Metrics Mohammed Alquliti Erisa Karafili BooJoong Kang XAI 29 0 0 12 May 2025
Unifying Perplexing Behaviors in Modified BP Attributions through Alignment Perspective Guanhua Zheng Jitao Sang Changsheng Xu AAML FAtt 67 0 0 14 Mar 2025
Knowledge-Augmented Explainable and Interpretable Learning for Anomaly Detection and Diagnosis Martin Atzmueller Tim Bohne Patricia Windler 85 0 0 28 Nov 2024
Explainable Artificial Intelligence for Medical Applications: A Review Qiyang Sun Alican Akman Björn Schuller 81 6 0 15 Nov 2024
IBO: Inpainting-Based Occlusion to Enhance Explainable Artificial Intelligence Evaluation in Histopathology Pardis Afshar Sajjad Hashembeiki Pouya Khani Emad Fatemizadeh M. Rohban 24 4 0 29 Aug 2024
Revocable Backdoor for Deep Model Trading Yiran Xu Nan Zhong Zhenxing Qian Xinpeng Zhang AAML 35 0 0 01 Aug 2024
Inpainting the Gaps: A Novel Framework for Evaluating Explanation Methods in Vision Transformers Lokesh Badisa Sumohana S. Channappayya 42 0 0 17 Jun 2024
Applications of Explainable artificial intelligence in Earth system science Feini Huang Shijie Jiang Lu Li Yongkun Zhang Ye Zhang Ruqing Zhang Qingliang Li Danxi Li Wei Shangguan Yongjiu Dai 30 2 0 12 Jun 2024
Backdoor-based Explainable AI Benchmark for High Fidelity Evaluation of Attribution Methods Peiyu Yang Naveed Akhtar Jiantong Jiang Ajmal Saeed Mian XAI 32 2 0 02 May 2024
Forward Learning for Gradient-based Black-box Saliency Map Generation Zeliang Zhang Mingqian Feng Jinyang Jiang Rongyi Zhu Yijie Peng Chenliang Xu FAtt 32 2 0 22 Mar 2024
Security and Privacy Challenges of Large Language Models: A Survey B. Das M. H. Amini Yanzhao Wu PILM ELM 19 103 0 30 Jan 2024
Manipulating Trajectory Prediction with Backdoors Kaouther Messaoud Kathrin Grosse Mickaël Chen Matthieu Cord Patrick Pérez Alexandre Alahi AAML LLMSV 29 0 0 21 Dec 2023
Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond Sidra Nasir Rizwan Ahmed Khan Samita Bai 17 29 0 31 Aug 2023
What's meant by explainable model: A Scoping Review Mallika Mainali Rosina O. Weber XAI 34 0 0 18 Jul 2023
Can We Trust Explainable AI Methods on ASR? An Evaluation on Phoneme Recognition Xiao-lan Wu P. Bell A. Rajan 19 5 0 29 May 2023
Backdoor Attack with Sparse and Invisible Trigger Yinghua Gao Yiming Li Xueluan Gong Zhifeng Li Shutao Xia Qianqian Wang AAML 13 20 0 11 May 2023
Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function Proposal M. Hashemi Ali Darejeh Francisco Cruz 40 3 0 07 Feb 2023
Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis Lukas Struppek Dominik Hintersdorf Kristian Kersting SILM 22 36 0 04 Nov 2022
SoK: Explainable Machine Learning for Computer Security Applications A. Nadeem D. Vos Clinton Cao Luca Pajola Simon Dieck Robert Baumgartner S. Verwer 34 40 0 22 Aug 2022
Towards A Holistic View of Bias in Machine Learning: Bridging Algorithmic Fairness and Imbalanced Learning Damien Dablain Bartosz Krawczyk Nitesh V. Chawla FaML 18 8 0 13 Jul 2022
Auditing Visualizations: Transparency Methods Struggle to Detect Anomalous Behavior Jean-Stanislas Denain Jacob Steinhardt AAML 39 7 0 27 Jun 2022
A Survey of Neural Trojan Attacks and Defenses in Deep Learning Jie Wang Ghulam Mubashar Hassan Naveed Akhtar AAML 26 24 0 15 Feb 2022
Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review F. Giuste Wenqi Shi Yuanda Zhu Tarun Naren Monica Isgut Ying Sha L. Tong Mitali S. Gupte May D. Wang 21 73 0 23 Dec 2021
Detection Accuracy for Evaluating Compositional Explanations of Units Sayo M. Makinwa Biagio La Rosa Roberto Capobianco FAtt CoGe 41 1 0 16 Sep 2021
Cross-Model Consensus of Explanations and Beyond for Image Classification Models: An Empirical Study Xuhong Li Haoyi Xiong Siyu Huang Shilei Ji Dejing Dou 14 10 0 02 Sep 2021
TRAPDOOR: Repurposing backdoors to detect dataset bias in machine learning-based genomic analysis Esha Sarkar Michail Maniatakos 24 3 0 14 Aug 2021
Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond Xuhong Li Haoyi Xiong Xingjian Li Xuanyu Wu Xiao Zhang Ji Liu Jiang Bian Dejing Dou AAML FaML XAI HAI 18 317 0 19 Mar 2021
Explainable Artificial Intelligence (XAI): An Engineering Perspective F. Hussain R. Hussain E. Hossain XAI 23 26 0 10 Jan 2021
BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations Xingyu Zhao Wei Huang Xiaowei Huang Valentin Robu David Flynn FAtt 26 92 0 05 Dec 2020
Trustworthy AI Richa Singh Mayank Vatsa N. Ratha 15 4 0 02 Nov 2020
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization Judy Borowski Roland S. Zimmermann Judith Schepers Robert Geirhos Thomas S. A. Wallis Matthias Bethge Wieland Brendel FAtt 36 7 0 23 Oct 2020
Backdoor Learning: A Survey Yiming Li Yong Jiang Zhifeng Li Shutao Xia AAML 45 586 0 17 Jul 2020
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 168 287 0 02 Dec 2018