v1v2 (latest)

Interpretation of Neural Networks is Fragile

AAAI Conference on Artificial Intelligence (AAAI), 2017

29 October 2017

Papers citing "Interpretation of Neural Networks is Fragile"

50 / 489 papers shown

Title
Beyond Model Interpretability: Socio-Structural Explanations in Machine LearningAi & Society (AS), 2024 Andrew Smart Atoosa Kasirzadeh 267 10 0 05 Sep 2024
Explanatory Model Monitoring to Understand the Effects of Feature Shifts on PerformanceKnowledge Discovery and Data Mining (KDD), 2024 Thomas Decker Alexander Koebler Michael Lebacher Ingo Thon Volker Tresp Florian Buettner 244 2 0 24 Aug 2024
Improving Network Interpretability via Explanation Consistency EvaluationIEEE transactions on multimedia (IEEE TMM), 2024 Hefeng Wu Hao Jiang Keze Wang Ziyi Tang Xianghuan He Liang Lin FAtt AAML 285 3 0 08 Aug 2024
Joint Universal Adversarial Perturbations with Interpretations Liang-bo Ning Zeyu Dai Wenqi Fan Jingran Su Chao Pan Luning Wang Qing Li AAML 290 3 0 03 Aug 2024
Algebraic Adversarial Attacks on Integrated Gradients Lachlan Simpson Federico Costanza Kyle Millar A. Cheng Cheng-Chew Lim Hong-Gunn Chew SILM AAML 400 4 0 23 Jul 2024
Interpretable Concept-Based Memory Reasoning David Debot Pietro Barbiero Francesco Giannini Gabriele Ciravegna Michelangelo Diligenti Giuseppe Marra LRM 285 13 0 22 Jul 2024
Auditing Local Explanations is Hard Robi Bhattacharjee U. V. Luxburg LRM MLAU FAtt 235 5 0 18 Jul 2024
Understanding Visual Feature Reliance through the Lens of Complexity Thomas Fel Louis Bethune Andrew Kyle Lampinen Thomas Serre Katherine Hermann FAtt CoGe 243 14 0 08 Jul 2024
CAT: Interpretable Concept-based Taylor Additive Models Viet Duong Qiong Wu Zhengyi Zhou Hongjue Zhao Chenxiang Luo Eric Zavesky Huaxiu Yao Huajie Shao FAtt 284 3 0 25 Jun 2024
Linearly-Interpretable Concept Embedding Models for Text Analysis Francesco De Santis Philippe Bich Gabriele Ciravegna Pietro Barbiero Danilo Giordano Tania Cerquitelli 279 1 0 20 Jun 2024
ProtoS-ViT: Visual foundation models for sparse self-explainable classifications Hugues Turbé Mina Bjelogrlic G. Mengaldo Christian Lovis ViT 281 8 0 14 Jun 2024
On the Robustness of Global Feature Effect Explanations Hubert Baniecki Giuseppe Casalicchio B. Bischl P. Biecek 300 4 0 13 Jun 2024
Explainable Graph Neural Networks Under Fire Zhong Li Simon Geisler Yuhang Wang Stephan Günnemann M. Leeuwen AAML 255 3 0 10 Jun 2024
Provably Better Explanations with Optimized Aggregation of Feature AttributionsInternational Conference on Machine Learning (ICML), 2024 Thomas Decker Ananta R. Bhattarai Jindong Gu Volker Tresp Florian Buettner 203 6 0 07 Jun 2024
Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model PredictionsInternational Conference on Machine Learning (ICML), 2024 Jingtan Wang Xiaoqiang Lin Rui Qiao Chuan-Sheng Foo Bryan Kian Hsiang Low TDI 184 9 0 07 Jun 2024
Expected Grad-CAM: Towards gradient faithfulness Vincenzo Buono Peyman Sheikholharam Mashhadi M. Rahat Prayag Tiwari Stefan Byttner FAtt 243 3 0 03 Jun 2024
Interpretable Prognostics with Concept Bottleneck Models Florent Forest Katharina Rombach Olga Fink 205 10 0 27 May 2024
AnyCBMs: How to Turn Any Black Box into a Concept Bottleneck Model Gabriele Dominici Pietro Barbiero Francesco Giannini M. Gjoreski Marc Langhenirich 204 5 0 26 May 2024
Exposing Image Classifier Shortcuts with Counterfactual Frequency (CoF) Tables James Hinns David Martens 291 4 0 24 May 2024
Why do explanations fail? A typology and discussion on failures in XAI Clara Bove Thibault Laugel Marie-Jeanne Lesot C. Tijus Marcin Detyniecki 237 8 0 22 May 2024
Safety in Graph Machine Learning: Threats and Safeguards Song Wang Yushun Dong Binchi Zhang Zihan Chen Xingbo Fu Yinhan He Cong Shen Chuxu Zhang Nitesh Chawla Wenlin Yao 264 11 0 17 May 2024
Manifold Integrated Gradients: Riemannian Geometry for Feature AttributionInternational Conference on Machine Learning (ICML), 2024 Eslam Zaher Maciej Trzaskowski Quan Nguyen Fred Roosta AAML 244 8 0 16 May 2024
Beyond the Black Box: Do More Complex Models Provide Superior XAI Explanations? Mateusz Cedro Marcin Chlebus 269 1 0 14 May 2024
$Certified $\ell_2$ Attribution Robustness via Uniformly Smoothed Attributions$ Certified $\ell_2$ Attribution Robustness via Uniformly Smoothed Attributions Fan Wang Adams Wai-Kin Kong 205 2 0 10 May 2024
Learned feature representations are biased by complexity, learning order, position, and more Andrew Kyle Lampinen Stephanie C. Y. Chan Katherine Hermann AI4CE FaML SSL OOD 255 18 0 09 May 2024
Explanation as a Watermark: Towards Harmless and Multi-bit Model Ownership Verification via Watermarking Feature Attribution Shuo Shao Yiming Li Hongwei Yao Yiling He Zhan Qin Kui Ren 234 31 0 08 May 2024
Stability of Explainable RecommendationACM Conference on Recommender Systems (RecSys), 2023 Sairamvinay Vijayaraghavan Prasant Mohapatra AAML 245 4 0 03 May 2024
Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots Xi Xin Giles Hooker Fei Huang AAML 258 8 0 29 Apr 2024
SIDEs: Separating Idealization from Deceptive Explanations in xAI Emily Sullivan 226 4 0 25 Apr 2024
Deep Neural Networks via Complex Network Theory: a Perspective Emanuele La Malfa G. Malfa Giuseppe Nicosia Vito Latora GNN 212 5 0 17 Apr 2024
Explainable Generative AI (GenXAI): A Survey, Conceptualization, and Research Agenda Johannes Schneider 242 73 0 15 Apr 2024
Exploring Explainability in Video Action Recognition Avinab Saha Shashank Gupta S. Ankireddy Karl Chahine Joydeep Ghosh 89 7 0 13 Apr 2024
PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis Dipkamal Bhusal Md Tanvirul Alam M. K. Veerabhadran Michael Clifford Sara Rampazzi Nidhi Rastogi AAML 214 5 0 12 Apr 2024
Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training Shizhan Gong Qi Dou Farzan Farnia FAtt 221 5 0 06 Apr 2024
Visual Concept Connectome (VCC): Open World Concept Discovery and their Interlayer Connections in Deep ModelsComputer Vision and Pattern Recognition (CVPR), 2024 M. Kowal Richard P. Wildes Konstantinos G. Derpanis GNN 283 14 0 02 Apr 2024
CAM-Based Methods Can See through Walls Magamed Taimeskhanov R. Sicre Damien Garreau 239 3 0 02 Apr 2024
Evaluating Explanatory Capabilities of Machine Learning Models in Medical Diagnostics: A Human-in-the-Loop Approach José Bobes-Bascarán E. Mosqueira-Rey Á. Fernández-Leal Elena Hernández-Pereira David Alonso-Ríos V. Moret-Bonillo Israel Figueirido-Arnoso Y. Vidal-Ínsua ELM 158 0 0 28 Mar 2024
The Anatomy of Adversarial Attacks: Concept-based XAI Dissection Georgii Mikriukov Gesina Schwalbe Franz Motzkus Korinna Bade AAML 203 1 0 25 Mar 2024
Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks Jon Vadillo Roberto Santana J. A. Lozano Marta Z. Kwiatkowska AAML BDL 491 1 0 20 Mar 2024
Gradient based Feature Attribution in Explainable AI: A Technical Review Yongjie Wang Tong Zhang Xu Guo Zhiqi Shen XAI 254 40 0 15 Mar 2024
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers Haoyang Liu Aditya Singh Yijiang Li Haohan Wang AAML ViT 333 1 0 15 Mar 2024
Towards White Box Deep Learning Maciej Satkiewicz AAML 430 1 0 14 Mar 2024
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape Tiejin Chen Wenwang Huang Linsey Pang Dongsheng Luo Hua Wei OOD 222 0 0 09 Mar 2024
XRL-Bench: A Benchmark for Evaluating and Comparing Explainable Reinforcement Learning Techniques Yu Xiong Zhipeng Hu Ye Huang Runze Wu Kai Guan ... Tianze Zhou Yujing Hu Haoyu Liu Tangjie Lyu Changjie Fan OffRL 356 2 0 20 Feb 2024
Probabilistic Shapley Value Modeling and Inference Mert Ketenci Inigo Urteaga Victor Alfonso Rodriguez Noémie Elhadad A. Perotte FAtt 305 0 0 06 Feb 2024
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data AttributionNeural Information Processing Systems (NeurIPS), 2024 Ian Covert Chanwoo Kim Su-In Lee James Zou Tatsunori Hashimoto TDI 313 14 0 29 Jan 2024
Respect the model: Fine-grained and Robust Explanation with Sharing Ratio DecompositionInternational Conference on Learning Representations (ICLR), 2024 Sangyu Han Yearim Kim Nojun Kwak AAML 219 4 0 25 Jan 2024
AttributionScanner: A Visual Analytics System for Model Validation with Metadata-Free Slice FindingIEEE Transactions on Visualization and Computer Graphics (TVCG), 2024 Xiwei Xuan Jorge Henrique Piazentin Ono Liang Gou Kwan-Liu Ma Liu Ren 244 7 0 12 Jan 2024
Manipulating Feature Visualizations with Gradient Slingshots Dilyara Bareeva Marina M.-C. Höhne Alexander Warnecke Lukas Pirch Klaus-Robert Müller Konrad Rieck Sebastian Lapuschkin Kirill Bykov AAML 371 6 0 11 Jan 2024
Towards Faithful Explanations for Text Classification with Robustness Improvement and Explanation Guided Training Dongfang Li Baotian Hu Qingcai Chen Shan He 279 8 0 29 Dec 2023