Interpretation of Neural Networks is Fragile

29 October 2017

Papers citing "Interpretation of Neural Networks is Fragile"

50 / 467 papers shown

Title
Gender Bias in Explainability: Investigating Performance Disparity in Post-hoc Methods Mahdi Dhaini Ege Erdogan Nils Feldhus Gjergji Kasneci 46 0 0 02 May 2025
Financial Fraud Detection with Entropy Computing Babak Emami Wesley Dyk David Haycraft Carrie Spear Lac Nguyen Nicholas Chancellor 45 0 0 14 Mar 2025
Axiomatic Explainer Globalness via Optimal Transport Davin Hill Josh Bone A. Masoomi Max Torop Jennifer Dy 100 1 0 13 Mar 2025
Birds look like cars: Adversarial analysis of intrinsically interpretable deep learning Hubert Baniecki P. Biecek AAML 80 0 0 11 Mar 2025
Conceptual Contrastive Edits in Textual and Vision-Language Retrieval Maria Lymperaiou Giorgos Stamou VLM 55 0 0 01 Mar 2025
Error-controlled non-additive interaction discovery in machine learning models Winston Chen Yifan Jiang William Stafford Noble Yang Young Lu 45 1 0 17 Feb 2025
Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks Jon Vadillo Roberto Santana J. A. Lozano Marta Z. Kwiatkowska BDL AAML 65 0 0 17 Feb 2025
The Effect of Similarity Measures on Accurate Stability Estimates for Local Surrogate Models in Text-based Explainable AI Christopher Burger Charles Walter Thai Le AAML 146 1 0 20 Jan 2025
Interpreting Deep Neural Network-Based Receiver Under Varying Signal-To-Noise Ratios Marko Tuononen Dani Korpi Ville Hautamäki FAtt 31 1 0 10 Jan 2025
Towards Robust and Accurate Stability Estimation of Local Surrogate Models in Text-based Explainable AI Christopher Burger Charles Walter Thai Le Lingwei Chen AAML 26 0 0 03 Jan 2025
Impact of Adversarial Attacks on Deep Learning Model Explainability Gazi Nazia Nur Mohammad Ahnaf Sadat AAML FAtt 77 0 0 15 Dec 2024
Quantized and Interpretable Learning Scheme for Deep Neural Networks in Classification Task Alireza Maleki Mahsa Lavaei Mohsen Bagheritabar Salar Beigzad Zahra Abadi MQ 67 0 0 05 Dec 2024
CatNet: Effective FDR Control in LSTM with Gaussian Mirrors and SHAP Feature Importance Jiaan Han Junxiao Chen Yanzhe Fu AI4TS 70 0 0 25 Nov 2024
Machines and Mathematical Mutations: Using GNNs to Characterize Quiver Mutation Classes Jesse He Helen Jenne Herman Chau Davis Brown Mark Raugas Sara Billey Henry Kvinge 23 3 0 12 Nov 2024
EXAGREE: Towards Explanation Agreement in Explainable Machine Learning Sichao Li Quanling Deng Amanda S. Barnard 37 0 0 04 Nov 2024
Directly Optimizing Explanations for Desired Properties Hiwot Belay Tadesse Alihan Hüyük Weiwei Pan Finale Doshi-Velez FAtt 43 0 0 31 Oct 2024
CausAdv: A Causal-based Framework for Detecting Adversarial Examples Hichem Debbi CML AAML 34 1 0 29 Oct 2024
Prototype-Based Methods in Explainable AI and Emerging Opportunities in the Geosciences Anushka Narayanan Karianne J. Bergen 27 1 0 22 Oct 2024
SSET: Swapping-Sliding Explanation for Time Series Classifiers in Affect Detection Nazanin Fouladgar Marjan Alirezaie Kary Främling AI4TS FAtt 16 0 0 16 Oct 2024
Unlearning-based Neural Interpretations Ching Lam Choi Alexandre Duplessis Serge Belongie FAtt 42 0 0 10 Oct 2024
Faithful Interpretation for Graph Neural Networks Lijie Hu Tianhao Huang Lu Yu Wanyu Lin Tianhang Zheng Di Wang 26 1 0 09 Oct 2024
A mechanistically interpretable neural network for regulatory genomics Alex Tseng Gökçen Eraslan Tommaso Biancalani Gabriele Scalia 19 0 0 08 Oct 2024
Understanding with toy surrogate models in machine learning Andrés Páez SyDa 24 0 0 08 Oct 2024
Mechanistic? Naomi Saphra Sarah Wiegreffe AI4CE 23 9 0 07 Oct 2024
Run-time Observation Interventions Make Vision-Language-Action Models More Visually Robust Asher Hancock Allen Z. Ren Anirudha Majumdar VLM 28 2 0 02 Oct 2024
Trustworthy Text-to-Image Diffusion Models: A Timely and Focused Survey Yi Zhang Zhen Chen Chih-Hong Cheng Wenjie Ruan Xiaowei Huang Dezong Zhao David Flynn Siddartha Khastgir Xingyu Zhao MedIm 33 3 0 26 Sep 2024
Faithfulness and the Notion of Adversarial Sensitivity in NLP Explanations Supriya Manna Niladri Sett AAML 29 2 0 26 Sep 2024
Deep Manifold Part 1: Anatomy of Neural Network Manifold Max Y. Ma Gen-Hua Shi PINN 3DPC 18 0 0 26 Sep 2024
Leveraging Local Structure for Improving Model Explanations: An Information Propagation Approach Ruo Yang Binghui Wang M. Bilgic FAtt 16 0 0 24 Sep 2024
Beyond Model Interpretability: Socio-Structural Explanations in Machine Learning Andrew Smart Atoosa Kasirzadeh 30 6 0 05 Sep 2024
Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance Thomas Decker Alexander Koebler Michael Lebacher Ingo Thon Volker Tresp Florian Buettner 26 1 0 24 Aug 2024
Improving Network Interpretability via Explanation Consistency Evaluation Hefeng Wu Hao Jiang Keze Wang Ziyi Tang Xianghuan He Liang Lin FAtt AAML 28 0 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 37 2 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 69 2 0 23 Jul 2024
Interpretable Concept-Based Memory Reasoning David Debot Pietro Barbiero Francesco Giannini Gabriele Ciravegna Michelangelo Diligenti Giuseppe Marra LRM 29 7 0 22 Jul 2024
Auditing Local Explanations is Hard Robi Bhattacharjee U. V. Luxburg LRM MLAU FAtt 34 2 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 30 6 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 22 2 0 25 Jun 2024
Self-supervised Interpretable Concept-based Models for Text Classification Francesco De Santis Philippe Bich Gabriele Ciravegna Pietro Barbiero Danilo Giordano Tania Cerquitelli 31 0 0 20 Jun 2024
ProtoS-ViT: Visual foundation models for sparse self-explainable classifications Hugues Turbé Mina Bjelogrlic G. Mengaldo Christian Lovis ViT 24 6 0 14 Jun 2024
On the Robustness of Global Feature Effect Explanations Hubert Baniecki Giuseppe Casalicchio Bernd Bischl Przemyslaw Biecek 23 2 0 13 Jun 2024
Explainable Graph Neural Networks Under Fire Zhong Li Simon Geisler Yuhang Wang Stephan Günnemann M. Leeuwen AAML 40 0 0 10 Jun 2024
Provably Better Explanations with Optimized Aggregation of Feature Attributions Thomas Decker Ananta R. Bhattarai Jindong Gu Volker Tresp Florian Buettner 22 2 0 07 Jun 2024
Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions Jingtan Wang Xiaoqiang Lin Rui Qiao Chuan-Sheng Foo Bryan Kian Hsiang Low TDI 35 3 0 07 Jun 2024
Expected Grad-CAM: Towards gradient faithfulness Vincenzo Buono Peyman Sheikholharam Mashhadi M. Rahat Prayag Tiwari Stefan Byttner FAtt 31 1 0 03 Jun 2024
Interpretable Prognostics with Concept Bottleneck Models Florent Forest Katharina Rombach Olga Fink 25 0 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 36 3 0 26 May 2024
Exposing Image Classifier Shortcuts with Counterfactual Frequency (CoF) Tables James Hinns David Martens 41 2 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 31 2 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 V. Chawla Jundong Li 45 7 0 17 May 2024