Towards Robust Interpretability with Self-Explaining Neural Networks

20 June 2018

David Alvarez-Melis

Papers citing "Towards Robust Interpretability with Self-Explaining Neural Networks"

50 / 507 papers shown

Title
DocVXQA: Context-Aware Visual Explanations for Document Question Answering Mohamed Ali Souibgui Changkyu Choi Andrey Barsky Kangsoo Jung Ernest Valveny Dimosthenis Karatzas 25 0 0 12 May 2025
Prediction via Shapley Value Regression Amr Alkhatib Roman Bresson Henrik Bostrom Michalis Vazirgiannis TDI FAtt 64 0 0 07 May 2025
PointExplainer: Towards Transparent Parkinson's Disease Diagnosis Xuechao Wang S. Nõmm Junqing Huang Kadri Medijainen A. Toomela Michael Ruzhansky AAML FAtt 26 0 0 04 May 2025
If Concept Bottlenecks are the Question, are Foundation Models the Answer? Nicola Debole Pietro Barbiero Francesco Giannini Andrea Passerini Stefano Teso Emanuele Marconato 131 0 0 28 Apr 2025
AI Awareness X. Li Haoyuan Shi Rongwu Xu Wei Xu 54 0 0 25 Apr 2025
Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts M. Zarlenga Gabriele Dominici Pietro Barbiero Z. Shams M. Jamnik KELM 158 0 0 24 Apr 2025
What Makes for a Good Saliency Map? Comparing Strategies for Evaluating Saliency Maps in Explainable AI (XAI) Felix Kares Timo Speith Hanwei Zhang Markus Langer FAtt XAI 38 0 0 23 Apr 2025
Leveraging multimodal explanatory annotations for video interpretation with Modality Specific Dataset Elisa Ancarani Julie Tores L. Sassatelli Rémy Sun Hui-Yin Wu F. Precioso 29 0 0 15 Apr 2025
ProtoECGNet: Case-Based Interpretable Deep Learning for Multi-Label ECG Classification with Contrastive Learning S. David Chen Thomas Statchen Michael C. Burkhart Nipun Bhandari Bashar Ramadan Brett Beaulieu-Jones 37 1 0 11 Apr 2025
Towards an Evaluation Framework for Explainable Artificial Intelligence Systems for Health and Well-being Esperança Amengual-Alcover Antoni Jaume-i-Capó Miquel Miró-Nicolau Gabriel Moyà Alcover Antonia Paniza-Fullana 32 0 0 11 Apr 2025
A constraints-based approach to fully interpretable neural networks for detecting learner behaviors Juan D. Pinto Luc Paquette 43 0 0 10 Apr 2025
V-CEM: Bridging Performance and Intervenability in Concept-based Models Francesco De Santis Gabriele Ciravegna Philippe Bich Danilo Giordano Tania Cerquitelli 32 0 0 04 Apr 2025
Interpretable Machine Learning in Physics: A Review Sebastian Johann Wetzel Seungwoong Ha Raban Iten Miriam Klopotek Ziming Liu AI4CE 80 0 0 30 Mar 2025
Language Guided Concept Bottleneck Models for Interpretable Continual Learning Lu Yu Haoyu Han Zhe Tao Hantao Yao Changsheng Xu CLL 60 0 0 30 Mar 2025
Self-Explaining Neural Networks for Business Process Monitoring Shahaf Bassan Shlomit Gur Sergey Zeltyn Konstantinos Mavrogiorgos Ron Eliav Dimosthenis Kyriazis 49 0 0 23 Mar 2025
Escaping Plato's Cave: Robust Conceptual Reasoning through Interpretable 3D Neural Object Volumes Nhi Pham Bernt Schiele Adam Kortylewski Jonas Fischer 61 0 0 17 Mar 2025
HyConEx: Hypernetwork classifier with counterfactual explanations Patryk Marszałek Ulvi Movsum-zada Oleksii Furman Kamil Ksiazek P. Spurek Marek Śmieja 58 0 0 16 Mar 2025
Causally Reliable Concept Bottleneck Models Giovanni De Felice Arianna Casanova Flores Francesco De Santis Silvia Santini Johannes Schneider Pietro Barbiero Alberto Termine 74 2 0 06 Mar 2025
ILLC: Iterative Layer-by-Layer Compression for Enhancing Structural Faithfulness in SpArX Ungsik Kim 51 0 0 05 Mar 2025
Controlled Model Debiasing through Minimal and Interpretable Updates Federico Di Gennaro Thibault Laugel Vincent Grari Marcin Detyniecki FaML 54 0 0 28 Feb 2025
QPM: Discrete Optimization for Globally Interpretable Image Classification Thomas Norrenbrock T. Kaiser Sovan Biswas R. Manuvinakurike Bodo Rosenhahn 55 0 0 27 Feb 2025
Evaluate with the Inverse: Efficient Approximation of Latent Explanation Quality Distribution Carlos Eiras-Franco Anna Hedström Marina M.-C. Höhne XAI 38 0 0 24 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
Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens Samuele Bortolotti Emanuele Marconato Paolo Morettin Andrea Passerini Stefano Teso 61 2 0 16 Feb 2025
Self-Explaining Hypergraph Neural Networks for Diagnosis Prediction Leisheng Yu Yanxiao Cai Minxing Zhang Xia Hu FAtt 144 0 0 15 Feb 2025
Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions H. Fokkema T. Erven Sara Magliacane 70 1 0 10 Feb 2025
VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance Divyansh Srivastava Beatriz Cabrero-Daniel Christian Berger VLM 62 8 0 17 Jan 2025
Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning Numair Sani Daniel Malinsky I. Shpitser CML 76 15 0 10 Jan 2025
Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations Xin-Chao Xu Yi Qin Lu Mi Hao Wang X. Li 74 9 0 03 Jan 2025
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics Lukas Klein Carsten T. Lüth U. Schlegel Till J. Bungert Mennatallah El-Assady Paul F. Jäger XAI ELM 42 2 0 03 Jan 2025
Concept Learning in the Wild: Towards Algorithmic Understanding of Neural Networks Elad Shohama Hadar Cohena Khalil Wattada Havana Rikab Dan Vilenchik 70 1 0 15 Dec 2024
Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation Davor Vukadin Petar Afrić Marin Šilić Goran Delač FAtt 93 2 0 12 Dec 2024
From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation Kristoffer Wickstrøm Marina M.-C. Höhne Anna Hedström AAML 79 2 0 07 Dec 2024
OMENN: One Matrix to Explain Neural Networks Adam Wróbel Mikołaj Janusz Bartosz Zieliñski Dawid Rymarczyk FAtt AAML 75 0 0 03 Dec 2024
Explaining the Impact of Training on Vision Models via Activation Clustering Ahcène Boubekki Samuel G. Fadel Sebastian Mair 89 0 0 29 Nov 2024
Establishing and Evaluating Trustworthy AI: Overview and Research Challenges Dominik Kowald S. Scher Viktoria Pammer-Schindler Peter Müllner Kerstin Waxnegger ... Andreas Truegler Eduardo E. Veas Roman Kern Tomislav Nad Simone Kopeinik 36 3 0 15 Nov 2024
Benchmarking XAI Explanations with Human-Aligned Evaluations Rémi Kazmierczak Steve Azzolin Eloise Berthier Anna Hedström Patricia Delhomme ... Goran Frehse Massimiliano Mancini Baptiste Caramiaux Andrea Passerini Gianni Franchi 23 1 0 04 Nov 2024
ParseCaps: An Interpretable Parsing Capsule Network for Medical Image Diagnosis Xinyu Geng Jiaming Wang Jun Xu MedIm 29 0 0 03 Nov 2024
Learning local discrete features in explainable-by-design convolutional neural networks Pantelis I. Kaplanoglou Konstantinos Diamantaras FAtt 49 1 0 31 Oct 2024
Directly Optimizing Explanations for Desired Properties Hiwot Belay Tadesse Alihan Hüyük Weiwei Pan Finale Doshi-Velez FAtt 43 0 0 31 Oct 2024
Gnothi Seauton: Empowering Faithful Self-Interpretability in Black-Box Transformers Shaobo Wang Hongxuan Tang Mingyang Wang H. Zhang Xuyang Liu Weiya Li Xuming Hu Linfeng Zhang 17 0 0 29 Oct 2024
Rethinking the Principle of Gradient Smooth Methods in Model Explanation Linjiang Zhou Chao Ma Zepeng Wang Xiaochuan Shi FAtt 24 0 0 10 Oct 2024
Unlearning-based Neural Interpretations Ching Lam Choi Alexandre Duplessis Serge Belongie FAtt 42 0 0 10 Oct 2024
Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks Junlin Hou Sicen Liu Yequan Bie Hongmei Wang Andong Tan Luyang Luo Hao Chen XAI 25 3 0 03 Oct 2024
Concept-Based Explanations in Computer Vision: Where Are We and Where Could We Go? Jae Hee Lee Georgii Mikriukov Gesina Schwalbe Stefan Wermter D. Wolter 52 2 0 20 Sep 2024
The Gaussian Discriminant Variational Autoencoder (GdVAE): A Self-Explainable Model with Counterfactual Explanations Anselm Haselhoff Kevin Trelenberg Fabian Küppers Jonas Schneider 29 1 0 19 Sep 2024
InfoDisent: Explainability of Image Classification Models by Information Disentanglement Łukasz Struski Dawid Rymarczyk Jacek Tabor 59 0 0 16 Sep 2024
MulCPred: Learning Multi-modal Concepts for Explainable Pedestrian Action Prediction Yan Feng Alexander Carballo Keisuke Fujii Robin Karlsson Ming Ding K. Takeda 31 0 0 14 Sep 2024
An Evaluation of Explanation Methods for Black-Box Detectors of Machine-Generated Text Loris Schoenegger Yuxi Xia Benjamin Roth FAtt 40 0 0 26 Aug 2024
Evaluating Explainable AI Methods in Deep Learning Models for Early Detection of Cerebral Palsy Kimji N. Pellano Inga Strümke Daniel Groos Lars Adde Espen Alexander F. Ihlen 18 2 0 14 Aug 2024