Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities

11 November 2021

Papers citing "Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities"

34 / 84 papers shown

Title
Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents Quentin Delfosse Sebastian Sztwiertnia M. Rothermel Wolfgang Stammer Kristian Kersting 41 18 0 11 Jan 2024
Combining Embedding-Based and Semantic-Based Models for Post-hoc Explanations in Recommender Systems Ngoc Luyen Lê Marie-Hélène Abel Philippe Gouspillou 13 5 0 09 Jan 2024
Integration Of Evolutionary Automated Machine Learning With Structural Sensitivity Analysis For Composite Pipelines Nikolay O. Nikitin Maiia Pinchuk Valerii Pokrovskii Peter Shevchenko Andrey Getmanov Yaroslav Aksenkin I. Revin Andrey Stebenkov Ekaterina Poslavskaya Anna V. Kaluzhnaya 18 0 0 22 Dec 2023
Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space Param S. Rajpura H. Cecotti Y. Meena 16 6 0 20 Dec 2023
User Friendly and Adaptable Discriminative AI: Using the Lessons from the Success of LLMs and Image Generation Models S. Nguyen Theja Tulabandhula M. Watson-Manheim 15 2 0 11 Dec 2023
Explainable AI is Responsible AI: How Explainability Creates Trustworthy and Socially Responsible Artificial Intelligence Stephanie B. Baker Wei Xiang XAI 23 5 0 04 Dec 2023
On the Relationship Between Interpretability and Explainability in Machine Learning Benjamin Leblanc Pascal Germain FaML 11 0 0 20 Nov 2023
A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions Junchao Wu Shu Yang Runzhe Zhan Yulin Yuan Derek F. Wong Lidia S. Chao DeLMO 11 22 0 23 Oct 2023
AI-based automated active learning for discovery of hidden dynamic processes: A use case in light microscopy Nils Friederich Angelo Jovin Yamachui Sitcheu Oliver Neumann Süheyla Eroglu-Kayikçi Roshan Prizak Lennart Hilbert Ralf Mikut 19 2 0 05 Oct 2023
Learning by Self-Explaining Wolfgang Stammer Felix Friedrich David Steinmann Manuel Brack Hikaru Shindo Kristian Kersting 18 7 0 15 Sep 2023
Viewing the process of generating counterfactuals as a source of knowledge: a new approach for explaining classifiers Vincent Lemaire Nathan Le Boudec Victor Guyomard Franccoise Fessant CML 8 0 0 08 Sep 2023
Learning to Intervene on Concept Bottlenecks David Steinmann Wolfgang Stammer Felix Friedrich Kristian Kersting 15 8 0 25 Aug 2023
Explainable Multi-View Deep Networks Methodology for Experimental Physics Nadav Schneider Muriel Tzdaka G. Sturm Guy Lazovski G. Bar G. Oren R. Gvishi Gal Oren 15 0 0 16 Aug 2023
FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security Analysis Yiling He Jian Lou Zhan Qin Kui Ren FAtt AAML 15 7 0 10 Aug 2023
Explainable machine learning to enable high-throughput electrical conductivity optimization and discovery of doped conjugated polymers Ji Wei Yoon Adithya Kumar Priyesh Kumar K. Hippalgaonkar J. Senthilnath Vijila Chellappan 11 4 0 08 Aug 2023
Identifying Explanation Needs of End-users: Applying and Extending the XAI Question Bank Lars Sipos Ulrike Schäfer Katrin Glinka Claudia Muller-Birn 10 4 0 18 Jul 2023
Evolutionary approaches to explainable machine learning Ryan Zhou Ting-Kuei Hu 17 7 0 23 Jun 2023
Multimodal Explainable Artificial Intelligence: A Comprehensive Review of Methodological Advances and Future Research Directions N. Rodis Christos Sardianos Panagiotis I. Radoglou-Grammatikis Panagiotis G. Sarigiannidis Iraklis Varlamis Georgios Th. Papadopoulos 12 8 0 09 Jun 2023
A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers Xiaoyan Zhao Yang Deng Min Yang Lingzhi Wang Rui Zhang Hong Cheng W. Lam Ying Shen Ruifeng Xu KELM 19 6 0 03 Jun 2023
Achieving Diversity in Counterfactual Explanations: a Review and Discussion Thibault Laugel Adulam Jeyasothy Marie-Jeanne Lesot Christophe Marsala Marcin Detyniecki CML 8 9 0 10 May 2023
Towards AI-Architecture Liberty: A Comprehensive Survey on Design and Generation of Virtual Architecture by Deep Learning Anqi Wang Jiahua Dong Lik-Hang Lee Jiachuan Shen Pan Hui 3DV AI4CE 17 0 0 30 Apr 2023
Multi-Modal Deep Learning for Credit Rating Prediction Using Text and Numerical Data Streams M. Tavakoli Rohitash Chandra Fengrui Tian Cristián Bravo 19 8 0 21 Apr 2023
A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation A. Khan Omkar Chaudhari Rohitash Chandra 13 163 0 06 Apr 2023
A Brief Review of Explainable Artificial Intelligence in Healthcare Zahra Sadeghi R. Alizadehsani M. Cifci Samina Kausar Rizwan Rehman ... A. Shoeibi H. Moosaei Milan Hladík Saeid Nahavandi P. Pardalos 6 13 0 04 Apr 2023
Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If Explorations Aditya Bhattacharya Jeroen Ooge Gregor Stiglic K. Verbert 11 30 0 21 Feb 2023
Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learning R. Heese Thore Gerlach Sascha Mucke Sabine Muller Matthias Jakobs Nico Piatkowski 16 17 0 22 Jan 2023
Deletion and Insertion Tests in Regression Models Naofumi Hama Masayoshi Mase Art B. Owen 11 8 0 25 May 2022
Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions Shahin Atakishiyev Mohammad Salameh Hengshuai Yao Randy Goebel 17 127 0 21 Dec 2021
A Survey of Knowledge Tracing: Models, Variants, and Applications Shuanghong Shen Qi Liu Zhenya Huang Yonghe Zheng Minghao Yin Minjuan Wang Enhong Chen KELM AI4Ed 14 6 0 06 May 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 159 463 0 31 Dec 2020
A Survey on Neural Network Interpretability Yu Zhang Peter Tiño A. Leonardis K. Tang FaML XAI 129 494 0 28 Dec 2020
Semantics of the Black-Box: Can knowledge graphs help make deep learning systems more interpretable and explainable? Manas Gaur Keyur Faldu A. Sheth 29 110 0 16 Oct 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 286 4,143 0 23 Aug 2019
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 222 3,658 0 28 Feb 2017